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feature/cboe-async: Refactor Cboe for Async (#5900)

Browse Source 
* refactor cboe for async

* codespell

* unused imports

* pylint

* more pylint

* platform metadata

* classmethod decorator

* test params

* intrinio quote

* test param names

* date in test needs to be a datetime.date not string

* make fmp unix timestamp tz-aware and normalize percent change

* different way of parsing datetime string

* recapture cboe equity historical test

* unused import

* index snapshot update

* black

* extension map

* pylint

* cboe pyproject.toml

* proposal to standardize equity_quote

* one more file

* removing changes on static assets

* index_historical

* index_historical again

* last_time -> last_timestamp

* obsolete router path

* fix tests

* test param

* restore market index deprecation that I forgot about

* fixing tests

---------

Co-authored-by: hjoaquim <h.joaquim@campus.fct.unl.pt>
This commit is contained in:
Danglewood
2024-01-22 07:17:42 -08:00
committed by GitHub
parent a9b4d2070f
commit e2f7e597fa
54 changed files with 18481 additions and 19318 deletions
Download Patch File Download Diff File Expand all files Collapse all files

25
openbb_platform/core/openbb_core/provider/standard_models/equity_historical.py
View File

@@ -8,7 +8,7 @@ from datetime import (
from typing import List, Optional, Set, Union
from dateutil import parser
from pydantic import Field, PositiveFloat, field_validator
from pydantic import Field, field_validator
from openbb_core.provider.abstract.data import Data
from openbb_core.provider.abstract.query_params import QueryParams
@@ -47,17 +47,24 @@ class EquityHistoricalQueryParams(QueryParams):
class EquityHistoricalData(Data):
"""Equity Historical Price Data."""
date: datetime = Field(description=DATA_DESCRIPTIONS.get("date", ""))
open: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("open", ""))
high: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("high", ""))
low: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("low", ""))
close: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("close", ""))
volume: Union[float, int] = Field(description=DATA_DESCRIPTIONS.get("volume", ""))
vwap: Optional[PositiveFloat] = Field(
date: Union[dateType, datetime] = Field(
description=DATA_DESCRIPTIONS.get("date", "")
)
open: float = Field(description=DATA_DESCRIPTIONS.get("open", ""))
high: float = Field(description=DATA_DESCRIPTIONS.get("high", ""))
low: float = Field(description=DATA_DESCRIPTIONS.get("low", ""))
close: float = Field(description=DATA_DESCRIPTIONS.get("close", ""))
volume: Optional[Union[float, int]] = Field(
default=None, description=DATA_DESCRIPTIONS.get("volume", "")
)
vwap: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("vwap", "")
)
@field_validator("date", mode="before", check_fields=False)
def date_validate(cls, v): # pylint: disable=E0213
"""Return formatted datetime."""
return parser.isoparse(str(v))
v = parser.isoparse(str(v))
if v.hour == 0 and v.minute == 0:
return v.date()
return v

50
openbb_platform/core/openbb_core/provider/standard_models/european_index_constituents.py
View File

@@ -1,50 +0,0 @@
"""European Index Constituents Standard Model."""
from typing import List, Set, Union
from pydantic import Field, field_validator
from openbb_core.provider.abstract.data import Data
from openbb_core.provider.abstract.query_params import QueryParams
from openbb_core.provider.utils.descriptions import (
DATA_DESCRIPTIONS,
QUERY_DESCRIPTIONS,
)
class EuropeanIndexConstituentsQueryParams(QueryParams):
"""European Index Constituents Query."""
symbol: str = Field(description=QUERY_DESCRIPTIONS.get("symbol", ""))
@field_validator("symbol", mode="before", check_fields=False)
def upper_symbol(cls, v: Union[str, List[str], Set[str]]):
"""Convert symbol to uppercase."""
if isinstance(v, str):
return v.upper()
return ",".join([symbol.upper() for symbol in list(v)])
class EuropeanIndexConstituentsData(Data):
"""European Index Constituents Data."""
symbol: str = Field(
description=DATA_DESCRIPTIONS.get("symbol", "")
+ " The symbol is the constituent company in the index."
)
price: float = Field(
description="Current price of the constituent company in the index."
)
open: float = Field(description=DATA_DESCRIPTIONS.get("open", ""))
high: float = Field(description=DATA_DESCRIPTIONS.get("high", ""))
low: float = Field(description=DATA_DESCRIPTIONS.get("low", ""))
close: float = Field(description=DATA_DESCRIPTIONS.get("close", ""))
volume: float = Field(description=DATA_DESCRIPTIONS.get("volume", ""))
@field_validator("symbol", mode="before", check_fields=False)
def upper_symbol(cls, v: Union[str, List[str], Set[str]]):
"""Convert symbol to uppercase."""
if isinstance(v, str):
return v.upper()
return ",".join([symbol.upper() for symbol in list(v)])

44
openbb_platform/core/openbb_core/provider/standard_models/european_indices.py
View File

@@ -1,44 +0,0 @@
"""European Indices Standard Model."""
from datetime import (
date as dateType,
datetime,
)
from typing import List, Optional, Set, Union
from pydantic import Field, field_validator
from openbb_core.provider.abstract.data import Data
from openbb_core.provider.abstract.query_params import QueryParams
from openbb_core.provider.utils.descriptions import (
DATA_DESCRIPTIONS,
QUERY_DESCRIPTIONS,
)
class EuropeanIndicesQueryParams(QueryParams):
"""European Indices Query."""
symbol: str = Field(description=QUERY_DESCRIPTIONS.get("symbol", ""))
start_date: Optional[dateType] = Field(
description=QUERY_DESCRIPTIONS.get("start_date", ""), default=None
)
end_date: Optional[dateType] = Field(
description=QUERY_DESCRIPTIONS.get("end_date", ""), default=None
)
@field_validator("symbol", mode="before", check_fields=False)
@classmethod
def upper_symbol(cls, v: Union[str, List[str], Set[str]]):
"""Convert symbol to uppercase."""
if isinstance(v, str):
return v.upper()
return ",".join([symbol.upper() for symbol in list(v)])
class EuropeanIndicesData(Data):
"""European Indices Data."""
date: datetime = Field(description=DATA_DESCRIPTIONS.get("date", ""))
close: float = Field(description=DATA_DESCRIPTIONS.get("close", ""))

31
openbb_platform/core/openbb_core/provider/standard_models/index_constituents.py
View File

@@ -1,8 +1,7 @@
"""Index Constituents Standard Model."""
from datetime import date
from typing import List, Literal, Optional, Set, Union
from typing import List, Optional, Set, Union
from pydantic import Field, field_validator
@@ -14,9 +13,8 @@ from openbb_core.provider.utils.descriptions import DATA_DESCRIPTIONS
class IndexConstituentsQueryParams(QueryParams):
"""Index Constituents Query."""
index: Literal["nasdaq", "sp500", "dowjones"] = Field(
default="dowjones",
description="Index for which we want to fetch the constituents.",
index: str = Field(
description="Index to fetch the constituents of.",
)
@@ -24,27 +22,8 @@ class IndexConstituentsData(Data):
"""Index Constituents Data."""
symbol: str = Field(description=DATA_DESCRIPTIONS.get("symbol", ""))
name: str = Field(description="Name of the constituent company in the index.")
sector: str = Field(
description="Sector the constituent company in the index belongs to."
)
sub_sector: Optional[str] = Field(
default=None,
description="Sub-sector the constituent company in the index belongs to.",
)
headquarter: Optional[str] = Field(
default=None,
description="Location of the headquarter of the constituent company in the index.",
)
date_first_added: Optional[Union[date, str]] = Field(
default=None, description="Date the constituent company was added to the index."
)
cik: int = Field(
description=DATA_DESCRIPTIONS.get("cik", ""),
)
founded: Optional[Union[date, str]] = Field(
default=None,
description="Founding year of the constituent company in the index.",
name: Optional[str] = Field(
default=None, description="Name of the constituent company in the index."
)
@field_validator("symbol", mode="before", check_fields=False)

18
openbb_platform/core/openbb_core/provider/standard_models/index_snapshots.py
View File

@@ -1,6 +1,6 @@
"""Index Snapshots Standard Model."""
from typing import Literal, Optional
from typing import Optional
from pydantic import Field
@@ -12,8 +12,8 @@ from openbb_core.provider.utils.descriptions import DATA_DESCRIPTIONS
class IndexSnapshotsQueryParams(QueryParams):
"""Index Snapshots Query."""
region: Optional[Literal["US", "EU"]] = Field(
description="The region to return. Currently supports US and EU.", default="US"
region: Optional[str] = Field(
default=None, description="The region to return data for - i.e. 'us' or 'eu'."
)
@@ -38,10 +38,16 @@ class IndexSnapshotsData(Data):
close: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("close", "")
)
volume: Optional[int] = Field(
default=None, description=DATA_DESCRIPTIONS.get("volume", "")
)
prev_close: Optional[float] = Field(
default=None, description="Previous closing price of the index."
default=None, description=DATA_DESCRIPTIONS.get("prev_close", "")
)
change: Optional[float] = Field(
default=None, description="Change in value of the index."
)
change: Optional[float] = Field(default=None, description="Change of the index.")
change_percent: Optional[float] = Field(
default=None, description="Change percent of the index."
default=None,
description="Change, in normalized percentage points, of the index.",
)

130
openbb_platform/core/openbb_core/provider/standard_models/options_chains.py
View File

@@ -1,6 +1,9 @@
"""Options Chains Standard Model."""
from datetime import date as dateType
from datetime import (
date as dateType,
datetime,
)
from typing import List, Optional, Set, Union
from pydantic import Field, field_validator
@@ -18,6 +21,7 @@ class OptionsChainsQueryParams(QueryParams):
symbol: str = Field(description=QUERY_DESCRIPTIONS.get("symbol", ""))
@classmethod
@field_validator("symbol", mode="before", check_fields=False)
def upper_symbol(cls, v: Union[str, List[str], Set[str]]):
"""Convert symbol to uppercase."""
@@ -29,30 +33,48 @@ class OptionsChainsQueryParams(QueryParams):
class OptionsChainsData(Data):
"""Options Chains Data."""
contract_symbol: str = Field(description="Contract symbol for the option.")
symbol: Optional[str] = Field(
description=DATA_DESCRIPTIONS.get("symbol", "")
+ " Here its the underlying symbol for the option.",
+ " Here, it is the underlying symbol for the option.",
default=None,
)
contract_symbol: str = Field(description="Contract symbol for the option.")
eod_date: Optional[dateType] = Field(
default=None, description="Date for which the options chains are returned."
)
expiration: dateType = Field(description="Expiration date of the contract.")
strike: float = Field(description="Strike price of the contract.")
option_type: str = Field(description="Call or Put.")
eod_date: Optional[dateType] = Field(
default=None, description="Date for which the options chains are returned."
open_interest: Optional[int] = Field(
default=None, description="Open interest on the contract."
)
close: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("close", "")
)
close_bid: Optional[float] = Field(
default=None, description="The closing bid price for the option that day."
)
close_ask: Optional[float] = Field(
default=None, description="The closing ask price for the option that day."
)
volume: Optional[float] = Field(
volume: Optional[int] = Field(
default=None, description=DATA_DESCRIPTIONS.get("volume", "")
)
theoretical_price: Optional[float] = Field(
default=None, description="Theoretical value of the option."
)
last_trade_price: Optional[float] = Field(
default=None, description="Last trade price of the option."
)
tick: Optional[str] = Field(
default=None, description="Whether the last tick was up or down in price."
)
bid: Optional[float] = Field(
default=None, description="Current bid price for the option."
)
bid_size: Optional[int] = Field(
default=None, description="Bid size for the option."
)
ask: Optional[float] = Field(
default=None, description="Current ask price for the option."
)
ask_size: Optional[int] = Field(
default=None, description="Ask size for the option."
)
mark: Optional[float] = Field(
default=None, description="The mid-price between the latest bid and ask."
)
open: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("open", "")
)
@@ -62,30 +84,64 @@ class OptionsChainsData(Data):
open_ask: Optional[float] = Field(
default=None, description="The opening ask price for the option that day."
)
open_interest: Optional[float] = Field(
default=None, description="Open interest on the contract."
)
high: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("high", "")
)
low: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("low", "")
)
mark: Optional[float] = Field(
default=None, description="The mid-price between the latest bid-ask spread."
)
ask_high: Optional[float] = Field(
default=None, description="The highest ask price for the option that day."
)
ask_low: Optional[float] = Field(
default=None, description="The lowest ask price for the option that day."
)
bid_high: Optional[float] = Field(
default=None, description="The highest bid price for the option that day."
)
ask_high: Optional[float] = Field(
default=None, description="The highest ask price for the option that day."
)
low: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("low", "")
)
bid_low: Optional[float] = Field(
default=None, description="The lowest bid price for the option that day."
)
ask_low: Optional[float] = Field(
default=None, description="The lowest ask price for the option that day."
)
close: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("close", "")
)
close_size: Optional[int] = Field(
default=None, description="The closing trade size for the option that day."
)
close_time: Optional[datetime] = Field(
default=None,
description="The time of the closing price for the option that day.",
)
close_bid: Optional[float] = Field(
default=None, description="The closing bid price for the option that day."
)
close_bid_size: Optional[int] = Field(
default=None, description="The closing bid size for the option that day."
)
close_bid_time: Optional[datetime] = Field(
default=None,
description="The time of the bid closing price for the option that day.",
)
close_ask: Optional[float] = Field(
default=None, description="The closing ask price for the option that day."
)
close_ask_size: Optional[int] = Field(
default=None, description="The closing ask size for the option that day."
)
close_ask_time: Optional[datetime] = Field(
default=None,
description="The time of the ask closing price for the option that day.",
)
prev_close: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("prev_close", "")
)
change: Optional[float] = Field(
default=None, description="The change in the price of the option."
)
change_percent: Optional[float] = Field(
default=None,
description="Change, in normalizezd percentage points, of the option.",
)
implied_volatility: Optional[float] = Field(
default=None, description="Implied volatility of the option."
)
@@ -93,10 +149,14 @@ class OptionsChainsData(Data):
gamma: Optional[float] = Field(default=None, description="Gamma of the option.")
theta: Optional[float] = Field(default=None, description="Theta of the option.")
vega: Optional[float] = Field(default=None, description="Vega of the option.")
rho: Optional[float] = Field(default=None, description="Rho of the option.")
@field_validator("date", mode="before", check_fields=False)
def upper_symbol(cls, v: Union[str, List[str], Set[str]]):
"""Convert symbol to uppercase."""
@field_validator("expiration", mode="before", check_fields=False)
@classmethod
def date_validate(cls, v): # pylint: disable=E0213
"""Return the datetime object from the date string"""
if isinstance(v, datetime):
return datetime.strftime(v, "%Y-%m-%d")
if isinstance(v, str):
return v.upper()
return ",".join([symbol.upper() for symbol in list(v)])
return datetime.strptime(v, "%Y-%m-%d")
return v

4
openbb_platform/extensions/derivatives/integration/test_derivatives_api.py
View File

@@ -24,7 +24,7 @@ def headers():
"params",
[
({"provider": "intrinio", "symbol": "AAPL", "date": "2023-01-25"}),
({"provider": "cboe", "symbol": "AAPL"}),
({"provider": "cboe", "symbol": "AAPL", "use_cache": False}),
],
)
@pytest.mark.integration
@@ -86,7 +86,7 @@ def test_derivatives_futures_historical(params, headers):
@parametrize(
"params",
[
({"provider": "cboe", "symbol": "VX", "date": "2023-01-25"}),
({"provider": "cboe", "symbol": "VX", "date": None}),
({"provider": "yfinance", "symbol": "ES", "date": "2023-08-01"}),
],
)

5
openbb_platform/extensions/derivatives/integration/test_derivatives_python.py
View File

@@ -20,9 +20,8 @@ def obb(pytestconfig):
@parametrize(
"params",
[
({"symbol": "AAPL"}),
({"provider": "intrinio", "symbol": "AAPL", "date": "2023-01-25"}),
({"provider": "cboe", "symbol": "AAPL"}),
({"provider": "cboe", "symbol": "AAPL", "use_cache": False}),
],
)
@pytest.mark.integration
@@ -75,7 +74,7 @@ def test_derivatives_futures_historical(params, obb):
@parametrize(
"params",
[
({"symbol": "VX", "date": "2023-01-25", "provider": "cboe"}),
({"symbol": "VX", "provider": "cboe", "date": None}),
({"provider": "yfinance", "symbol": "ES", "date": "2023-08-01"}),
],
)

5
openbb_platform/extensions/equity/integration/test_equity_api.py
View File

@@ -852,6 +852,7 @@ def test_equity_compare_peers(params, headers):
"start_date": "2023-01-01",
"end_date": "2023-01-02",
"interval": "1m",
"use_cache": False,
}
),
(
@@ -861,6 +862,7 @@ def test_equity_compare_peers(params, headers):
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"interval": "1d",
"use_cache": False,
}
),
(
@@ -1087,7 +1089,7 @@ def test_equity_fundamental_latest_attributes(params, headers):
@parametrize(
"params",
[
({"query": "AAPl", "is_symbol": True, "provider": "cboe"}),
({"query": "AAPl", "is_symbol": True, "provider": "cboe", "use_cache": False}),
({"query": "Apple", "provider": "sec", "use_cache": False, "is_fund": False}),
({"query": "", "provider": "nasdaq", "use_cache": False, "is_etf": True}),
({"query": "gold", "provider": "intrinio", "active": True, "limit": 100}),
@@ -1147,6 +1149,7 @@ def test_equity_screener(params, headers):
[
({"source": "iex", "provider": "intrinio", "symbol": "AAPL"}),
({"symbol": "AAPL", "provider": "fmp"}),
({"symbol": "AAPL", "provider": "cboe", "use_cache": False}),
({"symbol": "AAPL", "provider": "yfinance"}),
],
)

5
openbb_platform/extensions/equity/integration/test_equity_python.py
View File

@@ -806,6 +806,7 @@ def test_equity_compare_peers(params, obb):
"start_date": "2023-01-01",
"end_date": "2023-01-02",
"interval": "1m",
"use_cache": False,
}
),
(
@@ -815,6 +816,7 @@ def test_equity_compare_peers(params, obb):
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"interval": "1d",
"use_cache": False,
}
),
(
@@ -1037,7 +1039,7 @@ def test_equity_fundamental_latest_attributes(params, obb):
@parametrize(
"params",
[
({"query": "AAPL", "is_symbol": True, "provider": "cboe"}),
({"query": "AAPL", "is_symbol": True, "provider": "cboe", "use_cache": False}),
({"query": "Apple", "provider": "sec", "use_cache": False, "is_fund": False}),
({"query": "", "provider": "nasdaq", "use_cache": False, "is_etf": True}),
({"query": "gold", "provider": "intrinio", "active": True, "limit": 100}),
@@ -1092,6 +1094,7 @@ def test_equity_screener(params, obb):
({"symbol": "AAPL"}),
({"source": "iex", "provider": "intrinio", "symbol": "AAPL"}),
({"symbol": "AAPL", "provider": "fmp"}),
({"symbol": "AAPL", "provider": "cboe", "use_cache": False}),
({"symbol": "AAPL", "provider": "yfinance"}),
],
)

235
openbb_platform/extensions/index/integration/test_index_api.py
View File

@@ -21,7 +21,10 @@ def headers():
@parametrize(
"params",
[({"index": "dowjones", "provider": "fmp"})],
[
({"index": "dowjones", "provider": "fmp"}),
({"index": "BUKBUS", "provider": "cboe"}),
],
)
@pytest.mark.integration
def test_index_constituents(params, headers):
@@ -53,6 +56,7 @@ def test_index_constituents(params, headers):
"symbol": "AAVE100",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"use_cache": False,
}
),
(
@@ -62,121 +66,7 @@ def test_index_constituents(params, headers):
"symbol": "AAVE100",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
),
(
{
"interval": "1min",
"provider": "fmp",
"symbol": "^DJI",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"timeseries": 1,
"sort": "desc",
}
),
(
{
"interval": "1day",
"provider": "fmp",
"symbol": "^DJI",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"timeseries": 1,
"sort": "desc",
}
),
(
{
"timespan": "minute",
"sort": "desc",
"limit": 49999,
"adjusted": True,
"multiplier": 1,
"provider": "polygon",
"symbol": "NDX",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
),
(
{
"timespan": "day",
"sort": "desc",
"limit": 49999,
"adjusted": True,
"multiplier": 1,
"provider": "polygon",
"symbol": "NDX",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
),
(
{
"interval": "1d",
"period": "max",
"prepost": True,
"rounding": True,
"provider": "yfinance",
"symbol": "DJI",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
),
(
{
"provider": "intrinio",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"symbol": "$DJI",
"tag": "level",
"sort": "desc",
"limit": 100,
"type": None,
}
),
],
)
@pytest.mark.integration
def test_index_market(params, headers):
params = {p: v for p, v in params.items() if v}
query_str = get_querystring(params, [])
url = f"http://0.0.0.0:8000/api/v1/index/market?{query_str}"
result = requests.get(url, headers=headers, timeout=20)
assert isinstance(result, requests.Response)
assert result.status_code == 200
@parametrize(
"params",
[
(
{
"symbol": "^DJI",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"provider": "fmp",
"sort": "desc",
}
),
(
{
"interval": "1m",
"provider": "cboe",
"symbol": "AAVE100",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
),
(
{
"interval": "1d",
"provider": "cboe",
"symbol": "AAVE100",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"use_cache": False,
}
),
(
@@ -269,17 +159,77 @@ def test_index_price_historical(params, headers):
[
(
{
"symbol": "BUKBUS",
"symbol": "^DJI",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"provider": "cboe",
"provider": "fmp",
"sort": "desc",
}
),
(
{
"interval": "1m",
"provider": "cboe",
"symbol": "BUKBUS",
"symbol": "AAVE100",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"use_cache": True,
}
),
(
{
"interval": "1d",
"provider": "cboe",
"symbol": "AAVE100",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"use_cache": False,
}
),
(
{
"interval": "1min",
"provider": "fmp",
"symbol": "^DJI",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"timeseries": 1,
"sort": "desc",
}
),
(
{
"interval": "1day",
"provider": "fmp",
"symbol": "^DJI",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"timeseries": 1,
"sort": "desc",
}
),
(
{
"timespan": "minute",
"sort": "desc",
"limit": 49999,
"adjusted": True,
"multiplier": 1,
"provider": "polygon",
"symbol": "NDX",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
),
(
{
"timespan": "day",
"sort": "desc",
"limit": 49999,
"adjusted": True,
"multiplier": 1,
"provider": "polygon",
"symbol": "NDX",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
@@ -287,36 +237,36 @@ def test_index_price_historical(params, headers):
(
{
"interval": "1d",
"provider": "cboe",
"symbol": "BUKBUS",
"period": "max",
"prepost": True,
"rounding": True,
"provider": "yfinance",
"symbol": "DJI",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
),
(
{
"provider": "intrinio",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"symbol": "$DJI",
"tag": "level",
"sort": "desc",
"limit": 100,
"type": None,
}
),
],
)
@pytest.mark.integration
def test_index_european(params, headers):
def test_index_market(params, headers):
params = {p: v for p, v in params.items() if v}
query_str = get_querystring(params, [])
url = f"http://0.0.0.0:8000/api/v1/index/european?{query_str}"
result = requests.get(url, headers=headers, timeout=10)
assert isinstance(result, requests.Response)
assert result.status_code == 200
@parametrize(
"params",
[({"symbol": "BUKBUS", "provider": "cboe"})],
)
@pytest.mark.integration
def test_index_european_constituents(params, headers):
params = {p: v for p, v in params.items() if v}
query_str = get_querystring(params, [])
url = f"http://0.0.0.0:8000/api/v1/index/european_constituents?{query_str}"
result = requests.get(url, headers=headers, timeout=10)
url = f"http://0.0.0.0:8000/api/v1/index/market?{query_str}"
result = requests.get(url, headers=headers, timeout=20)
assert isinstance(result, requests.Response)
assert result.status_code == 200
@@ -324,7 +274,7 @@ def test_index_european_constituents(params, headers):
@parametrize(
"params",
[
({"europe": True, "provider": "cboe"}),
({"provider": "cboe", "use_cache": False}),
({"provider": "fmp"}),
({"provider": "yfinance"}),
],
@@ -343,8 +293,7 @@ def test_index_available(params, headers):
@parametrize(
"params",
[
({"query": "D", "is_symbol": True, "provider": "cboe"}),
({"europe": True, "provider": "cboe", "query": "A", "is_symbol": False}),
({"query": "D", "is_symbol": True, "provider": "cboe", "use_cache": False}),
],
)
@pytest.mark.integration
@@ -360,7 +309,7 @@ def test_index_search(params, headers):
@parametrize(
"params",
[({"provider": "cboe", "region": "US"})],
[({"provider": "cboe", "region": "us"})],
)
@pytest.mark.integration
def test_index_snapshots(params, headers):

229
openbb_platform/extensions/index/integration/test_index_python.py
View File

@@ -21,7 +21,8 @@ def obb(pytestconfig): # pylint: disable=inconsistent-return-statements
@parametrize(
"params",
[
({"index": "dowjones"}),
({"index": "dowjones", "provider": "fmp"}),
({"index": "BUKBUS", "provider": "cboe"}),
],
)
@pytest.mark.integration
@@ -35,123 +36,6 @@ def test_index_constituents(params, obb):
@parametrize(
"params",
[
(
{
"symbol": "AAVE100",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
),
(
{
"interval": "1m",
"provider": "cboe",
"symbol": "AAVE100",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
),
(
{
"interval": "1d",
"provider": "cboe",
"symbol": "AAVE100",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
),
(
{
"interval": "1min",
"provider": "fmp",
"symbol": "^DJI",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"timeseries": 1,
"sort": "desc",
}
),
(
{
"interval": "1day",
"provider": "fmp",
"symbol": "^DJI",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"timeseries": 1,
"sort": "desc",
}
),
(
{
"timespan": "minute",
"sort": "desc",
"limit": 49999,
"adjusted": True,
"multiplier": 1,
"provider": "polygon",
"symbol": "NDX",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
),
(
{
"timespan": "day",
"sort": "desc",
"limit": 49999,
"adjusted": True,
"multiplier": 1,
"provider": "polygon",
"symbol": "NDX",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
),
(
{
"interval": "1d",
"period": "max",
"prepost": True,
"rounding": True,
"provider": "yfinance",
"symbol": "DJI",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
),
(
{
"provider": "intrinio",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"symbol": "$DJI",
"tag": "level",
"sort": "desc",
"limit": 100,
"type": None,
}
),
],
)
@pytest.mark.integration
def test_index_market(params, obb):
result = obb.index.market(**params)
assert result
assert isinstance(result, OBBject)
assert len(result.results) > 0
@parametrize(
"params",
[
(
{
"symbol": "AAVE100",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
),
(
{
"interval": "1m",
@@ -159,6 +43,7 @@ def test_index_market(params, obb):
"symbol": "AAVE100",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"use_cache": False,
}
),
(
@@ -168,6 +53,7 @@ def test_index_market(params, obb):
"symbol": "AAVE100",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"use_cache": False,
}
),
(
@@ -257,7 +143,7 @@ def test_index_price_historical(params, obb):
[
(
{
"symbol": "BUKBUS",
"symbol": "AAVE100",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
@@ -266,7 +152,66 @@ def test_index_price_historical(params, obb):
{
"interval": "1m",
"provider": "cboe",
"symbol": "BUKBUS",
"symbol": "AAVE100",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"use_cache": True,
}
),
(
{
"interval": "1d",
"provider": "cboe",
"symbol": "AAVE100",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"use_cache": False,
}
),
(
{
"interval": "1min",
"provider": "fmp",
"symbol": "^DJI",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"timeseries": 1,
"sort": "desc",
}
),
(
{
"interval": "1day",
"provider": "fmp",
"symbol": "^DJI",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"timeseries": 1,
"sort": "desc",
}
),
(
{
"timespan": "minute",
"sort": "desc",
"limit": 49999,
"adjusted": True,
"multiplier": 1,
"provider": "polygon",
"symbol": "NDX",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
),
(
{
"timespan": "day",
"sort": "desc",
"limit": 49999,
"adjusted": True,
"multiplier": 1,
"provider": "polygon",
"symbol": "NDX",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
@@ -274,31 +219,32 @@ def test_index_price_historical(params, obb):
(
{
"interval": "1d",
"provider": "cboe",
"symbol": "BUKBUS",
"period": "max",
"prepost": True,
"rounding": True,
"provider": "yfinance",
"symbol": "DJI",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
}
),
(
{
"provider": "intrinio",
"start_date": "2023-01-01",
"end_date": "2023-06-06",
"symbol": "$DJI",
"tag": "level",
"sort": "desc",
"limit": 100,
"type": None,
}
),
],
)
@pytest.mark.integration
def test_index_european(params, obb):
result = obb.index.european(**params)
assert result
assert isinstance(result, OBBject)
assert len(result.results) > 0
@parametrize(
"params",
[
({"symbol": "BUKBUS", "provider": "cboe"}),
],
)
@pytest.mark.integration
def test_index_european_constituents(params, obb):
result = obb.index.european_constituents(**params)
def test_index_market(params, obb):
result = obb.index.market(**params)
assert result
assert isinstance(result, OBBject)
assert len(result.results) > 0
@@ -308,7 +254,7 @@ def test_index_european_constituents(params, obb):
"params",
[
({}),
({"europe": True, "provider": "cboe"}),
({"provider": "cboe", "use_cache": False}),
({"provider": "fmp"}),
({"provider": "yfinance"}),
],
@@ -324,8 +270,7 @@ def test_index_available(params, obb):
@parametrize(
"params",
[
({"query": "D", "is_symbol": True}),
({"europe": True, "provider": "cboe", "query": "A", "is_symbol": False}),
({"query": "D", "is_symbol": True, "use_cache": False, "provider": "cboe"}),
],
)
@pytest.mark.integration
@@ -339,7 +284,7 @@ def test_index_search(params, obb):
@parametrize(
"params",
[
({"region": "US"}),
({"region": "us", "provider": "cboe"}),
],
)
@pytest.mark.integration

22
openbb_platform/extensions/index/openbb_index/index_router.py
View File

@@ -33,17 +33,6 @@ async def market(
return await OBBject.from_query(Query(**locals()))
@router.command(model="EuropeanIndices")
async def european(
cc: CommandContext,
provider_choices: ProviderChoices,
standard_params: StandardParams,
extra_params: ExtraParams,
) -> OBBject[BaseModel]:
"""Historical European Indices."""
return await OBBject.from_query(Query(**locals()))
@router.command(model="IndexConstituents")
async def constituents(
cc: CommandContext,
@@ -55,17 +44,6 @@ async def constituents(
return await OBBject.from_query(Query(**locals()))
@router.command(model="EuropeanIndexConstituents")
async def european_constituents(
cc: CommandContext,
provider_choices: ProviderChoices,
standard_params: StandardParams,
extra_params: ExtraParams,
) -> OBBject[BaseModel]:
"""European Index Constituents. Constituents of select european indices."""
return await OBBject.from_query(Query(**locals()))
@router.command(model="IndexSnapshots")
async def snapshots(
cc: CommandContext,

48
openbb_platform/poetry.lock generated vendored
View File

@@ -898,13 +898,13 @@ files = [
[[package]]
name = "jsonschema"
version = "4.21.0"
version = "4.21.1"
description = "An implementation of JSON Schema validation for Python"
optional = true
python-versions = ">=3.8"
files = [
{file = "jsonschema-4.21.0-py3-none-any.whl", hash = "sha256:70a09719d375c0a2874571b363c8a24be7df8071b80c9aa76bc4551e7297c63c"},
{file = "jsonschema-4.21.0.tar.gz", hash = "sha256:3ba18e27f7491ea4a1b22edce00fb820eec968d397feb3f9cb61d5894bb38167"},
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{file = "jsonschema-4.21.1.tar.gz", hash = "sha256:85727c00279f5fa6bedbe6238d2aa6403bedd8b4864ab11207d07df3cc1b2ee5"},
]
[package.dependencies]
@@ -2111,13 +2111,13 @@ testing = ["pytest", "pytest-benchmark"]
[[package]]
name = "posthog"
version = "3.3.1"
version = "3.3.2"
description = "Integrate PostHog into any python application."
optional = false
python-versions = "*"
files = [
{file = "posthog-3.3.1-py2.py3-none-any.whl", hash = "sha256:5f53b232acb680a0389e372db5f786061a18386b8b5324bddcc64eff9fdb319b"},
{file = "posthog-3.3.1.tar.gz", hash = "sha256:252cb6ab5cbe7ff002753f34fb647721b3af75034b4a5a631317ebf3db58fe59"},
{file = "posthog-3.3.2-py2.py3-none-any.whl", hash = "sha256:14fb43ea95c40b353db59c49af2c09ff15188aa2963f48091fc7912fa9375263"},
{file = "posthog-3.3.2.tar.gz", hash = "sha256:734bf89f3c372605a8bbf2b07f600885287209145d747b09ccd004c59834750e"},
]
[package.dependencies]
@@ -2683,28 +2683,28 @@ pyasn1 = ">=0.1.3"
[[package]]
name = "ruff"
version = "0.1.13"
version = "0.1.14"
description = "An extremely fast Python linter and code formatter, written in Rust."
optional = false
python-versions = ">=3.7"
files = [
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23
openbb_platform/providers/cboe/openbb_cboe/__init__.py
View File

@@ -1,25 +1,19 @@
"""CBOE provider module."""
"""Cboe provider module."""
from openbb_cboe.models.available_indices import CboeAvailableIndicesFetcher
from openbb_cboe.models.equity_historical import CboeEquityHistoricalFetcher
from openbb_cboe.models.equity_info import CboeEquityInfoFetcher
from openbb_cboe.models.equity_quote import CboeEquityQuoteFetcher
from openbb_cboe.models.equity_search import CboeEquitySearchFetcher
from openbb_cboe.models.european_index_constituents import (
CboeEuropeanIndexConstituentsFetcher,
)
from openbb_cboe.models.european_indices import (
CboeEuropeanIndicesFetcher,
)
from openbb_cboe.models.futures_curve import CboeFuturesCurveFetcher
from openbb_cboe.models.index_constituents import (
CboeIndexConstituentsFetcher,
)
from openbb_cboe.models.index_historical import (
CboeIndexHistoricalFetcher,
)
from openbb_cboe.models.index_search import CboeIndexSearchFetcher
from openbb_cboe.models.index_snapshots import CboeIndexSnapshotsFetcher
from openbb_cboe.models.market_indices import (
CboeMarketIndicesFetcher,
)
from openbb_cboe.models.options_chains import CboeOptionsChainsFetcher
from openbb_core.provider.abstract.provider import Provider
@@ -33,15 +27,14 @@ cboe_provider = Provider(
fetcher_dict={
"AvailableIndices": CboeAvailableIndicesFetcher,
"EquityHistorical": CboeEquityHistoricalFetcher,
"EquityInfo": CboeEquityInfoFetcher,
"EquityQuote": CboeEquityQuoteFetcher,
"EquitySearch": CboeEquitySearchFetcher,
"EuropeanIndexConstituents": CboeEuropeanIndexConstituentsFetcher,
"EuropeanIndices": CboeEuropeanIndicesFetcher,
"IndexConstituents": CboeIndexConstituentsFetcher,
"FuturesCurve": CboeFuturesCurveFetcher,
"IndexHistorical": CboeIndexHistoricalFetcher,
"IndexSearch": CboeIndexSearchFetcher,
"IndexSnapshots": CboeIndexSnapshotsFetcher,
"MarketIndices": CboeMarketIndicesFetcher,
"MarketIndices": CboeIndexHistoricalFetcher,
"OptionsChains": CboeOptionsChainsFetcher,
},
)

41
openbb_platform/providers/cboe/openbb_cboe/models/available_indices.py
View File

@@ -1,9 +1,9 @@
"""CBOE Available Indices Model."""
"""Cboe Available Indices Model."""
from datetime import time
from typing import Any, Dict, List, Optional
from openbb_cboe.utils.helpers import Europe, get_cboe_index_directory
from openbb_cboe.utils.helpers import get_index_directory
from openbb_core.provider.abstract.fetcher import Fetcher
from openbb_core.provider.standard_models.available_indices import (
AvailableIndicesData,
@@ -13,31 +13,30 @@ from pydantic import Field
class CboeAvailableIndicesQueryParams(AvailableIndicesQueryParams):
"""CBOE Available Indices Query.
"""Cboe Available Indices Query.
Source: https://www.cboe.com/europe/indices/
Source: https://www.cboe.com/
"""
europe: bool = Field(
description="Filter for European indices. False for US indices.", default=False
use_cache: bool = Field(
default=True,
description="When True, the Cboe Index directory will be cached for 24 hours."
+ " Set as False to bypass.",
)
class CboeAvailableIndicesData(AvailableIndicesData):
"""CBOE Available Indices Data.
"""Cboe Available Indices Data.
Source: https://www.cboe.com/europe/indices/
Source: https://www.cboe.com/
"""
isin: Optional[str] = Field(
default=None,
description="ISIN code for the index. Valid only for European indices.",
)
region: Optional[str] = Field(
default=None,
description="Region for the index. Valid only for European indices",
)
__alias_dict__ = {
"symbol": "index_symbol",
"data_delay": "mkt_data_delay",
"open_time": "calc_start_time",
"close_time": "calc_end_time",
}
symbol: Optional[str] = Field(description="Symbol for the index.")
@@ -94,15 +93,15 @@ class CboeAvailableIndicesFetcher(
return CboeAvailableIndicesQueryParams(**params)
@staticmethod
def extract_data(
async def aextract_data(
query: CboeAvailableIndicesQueryParams,
credentials: Optional[Dict[str, str]],
**kwargs: Any,
) -> List[Dict]:
"""Return the raw data from the CBOE endpoint."""
if query.europe is True:
return Europe.list_indices()
return get_cboe_index_directory().sort_index().reset_index().to_dict("records")
data = await get_index_directory(use_cache=query.use_cache, **kwargs)
return data.to_dict("records")
@staticmethod
def transform_data(

317
openbb_platform/providers/cboe/openbb_cboe/models/equity_historical.py
View File

@@ -1,15 +1,13 @@
"""CBOE Equity Historical Price Model."""
"""Cboe Equity Historical Price Model."""
import contextlib
import warnings
from datetime import datetime, timedelta
from typing import Any, Dict, List, Literal, Optional
import pandas as pd
from openbb_cboe.utils.helpers import (
TICKER_EXCEPTIONS,
get_cboe_directory,
get_cboe_index_directory,
get_ticker_info,
get_index_directory,
)
from openbb_core.provider.abstract.fetcher import Fetcher
from openbb_core.provider.standard_models.equity_historical import (
@@ -17,33 +15,52 @@ from openbb_core.provider.standard_models.equity_historical import (
EquityHistoricalQueryParams,
)
from openbb_core.provider.utils.descriptions import QUERY_DESCRIPTIONS
from openbb_core.provider.utils.helpers import make_request
from openbb_core.provider.utils.errors import EmptyDataError
from openbb_core.provider.utils.helpers import amake_requests
from pandas import DataFrame, Series, concat, to_datetime
from pydantic import Field
_warn = warnings.warn
class CboeEquityHistoricalQueryParams(EquityHistoricalQueryParams):
"""CBOE Equity Historical Price Query.
"""
Cboe Equity Historical Price Query
Source: https://www.cboe.com/
"""
interval: Literal["1m", "1d"] = Field(
default="1d", description=QUERY_DESCRIPTIONS.get("interval", "")
default="1d",
description=(
QUERY_DESCRIPTIONS.get("interval", "")
+ " The most recent trading day is not including in daily historical data."
+ " Intraday data is only available for the most recent trading day at 1 minute intervals."
),
)
use_cache: bool = Field(
default=True,
description="When True, the company directories will be cached for 24 hours and are used to validate symbols."
+ " The results of the function are not cached. Set as False to bypass.",
)
class CboeEquityHistoricalData(EquityHistoricalData):
"""CBOE Equity Historical Price Data."""
"""Cboe Equity Historical Price Data."""
calls_volume: Optional[float] = Field(
__alias_dict__ = {
"volume": "stock_volume",
}
calls_volume: Optional[int] = Field(
default=None,
description="Number of calls traded during the most recent trading period. Only valid if interval is 1m.",
)
puts_volume: Optional[float] = Field(
puts_volume: Optional[int] = Field(
default=None,
description="Number of puts traded during the most recent trading period. Only valid if interval is 1m.",
)
total_options_volume: Optional[float] = Field(
total_options_volume: Optional[int] = Field(
default=None,
description="Total number of options traded during the most recent trading period. Only valid if interval is 1m.",
)
@@ -59,179 +76,131 @@ class CboeEquityHistoricalFetcher(
@staticmethod
def transform_query(params: Dict[str, Any]) -> CboeEquityHistoricalQueryParams:
"""Transform the query. Setting the start and end dates for a 1 year period."""
return CboeEquityHistoricalQueryParams(**params)
"""Transform the query."""
transformed_params = params.copy()
now = datetime.now()
if (
len(params.get("symbol", "").split(",")) > 1
and params.get("start_date") is None
):
transformed_params["start_date"] = (
transformed_params["start_date"]
if transformed_params["start_date"]
else (now - timedelta(days=720)).strftime("%Y-%m-%d")
)
if transformed_params.get("start_date") is None:
transformed_params["start_date"] = (
transformed_params["start_date"]
if transformed_params.get("start_date")
else "1950-01-01"
)
if params.get("end_date") is None:
transformed_params["end_date"] = (
transformed_params["end_date"]
if transformed_params.get("end_date")
else now.strftime("%Y-%m-%d")
)
return CboeEquityHistoricalQueryParams(**transformed_params)
@staticmethod
def extract_data(
query: CboeEquityHistoricalQueryParams, # pylint: disable=unused-argument
async def aextract_data(
query: CboeEquityHistoricalQueryParams,
credentials: Optional[Dict[str, str]],
**kwargs: Any,
) -> List[Dict]:
"""Return the raw data from the CBOE endpoint."""
# Symbol directories are cached for seven days and are used for error handling and URL generation.
SYMBOLS = get_cboe_directory()
INDEXES = get_cboe_index_directory().index.to_list()
multi = pd.DataFrame()
now = datetime.now()
tickers = (
query.symbol.split(",") if "," in query.symbol else [query.symbol.upper()]
)
if len(tickers) > 1:
query.start_date = (
query.start_date if query.start_date else now - timedelta(days=720)
"""Return the raw data from the Cboe endpoint."""
symbols = query.symbol.split(",")
INDEXES = await get_index_directory(use_cache=query.use_cache)
INDEXES = INDEXES.set_index("index_symbol")
INTERVAL_DICT = {"1m": "intraday", "1d": "historical"}
def _generate_historical_prices_url(
symbol,
interval_type: Literal["intraday", "historical"] = "historical",
) -> str:
"""Generate the URL for the data."""
if symbol.replace("^", "") in TICKER_EXCEPTIONS:
interval_type = "intraday" if len(symbols) == 1 else "historical"
_warn(
"Only the most recent trading day is available for this ticker, "
+ symbol
)
base_url: str = (
f"https://cdn.cboe.com/api/global/delayed_quotes/charts/{interval_type}"
)
if len(tickers) == 1:
query.start_date = (
query.start_date if query.start_date else now - timedelta(days=50000)
)
query.end_date = query.end_date if query.end_date else now
def get_one(symbol, start_date, end_date, interval):
symbol = symbol.upper()
if "^" in symbol:
symbol = symbol.replace("^", "")
if len(tickers) == 1 and symbol == "NDX":
raise RuntimeError("NDX is not supported by this function.")
data = pd.DataFrame()
if symbol not in SYMBOLS.index and symbol not in INDEXES:
raise RuntimeError(
f"The symbol, {symbol}, was not found in the CBOE directory. Use `search()`."
)
def __generate_historical_prices_url(
symbol,
data_type: Optional[Literal["intraday", "historical"]] = "historical",
) -> str:
"""Generate the final URL for historical prices data."""
url: str = (
f"https://cdn.cboe.com/api/global/delayed_quotes/charts/{data_type}"
)
url = (
url + f"/_{symbol}.json"
if symbol in TICKER_EXCEPTIONS or symbol in INDEXES
else url + f"/{symbol}.json"
)
return url
url = (
__generate_historical_prices_url(symbol, "intraday")
if interval == "1m"
else __generate_historical_prices_url(symbol)
base_url + f"/_{symbol.replace('^', '')}.json"
if symbol.replace("^", "") in TICKER_EXCEPTIONS
or symbol.replace("^", "") in INDEXES.index
else base_url + f"/{symbol.replace('^', '')}.json"
)
r = make_request(url)
return url
if r.status_code != 200:
raise RuntimeError(r.status_code)
if interval == "1d":
data = (
pd.DataFrame(r.json()["data"])[
["date", "open", "high", "low", "close", "volume"]
]
).set_index("date")
# Fill in missing data from current or most recent trading session.
today = pd.to_datetime(datetime.now().date())
if today.weekday() > 4:
day_minus = today.weekday() - 4
today = pd.to_datetime(today - timedelta(days=day_minus))
if today != data.index[-1]:
_today = pd.Series(get_ticker_info(symbol))
today_df = pd.Series(dtype="object")
today_df["open"] = round(_today["open"], 2)
today_df["high"] = round(_today["high"], 2)
today_df["low"] = round(_today["low"], 2)
today_df["close"] = round(_today["close"], 2)
if symbol not in INDEXES and symbol not in TICKER_EXCEPTIONS:
data = data[data["volume"] > 0]
today_df["volume"] = _today["volume"]
today_df["date"] = today.date()
today_df = pd.DataFrame(today_df).transpose().set_index("date")
data = pd.concat([data, today_df], axis=0)
# If ticker is an index there is no volume data and the types must be set.
if symbol in INDEXES or symbol in TICKER_EXCEPTIONS:
data = data[["open", "high", "low", "close", "volume"]]
data["open"] = round(data.open.astype(float), 2)
data["high"] = round(data.high.astype(float), 2)
data["low"] = round(data.low.astype(float), 2)
data["close"] = round(data.close.astype(float), 2)
data["volume"] = 0
data.index = pd.to_datetime(data.index)
data = data[data["open"] > 0]
data = data[
(data.index >= pd.to_datetime(start_date))
& (data.index <= pd.to_datetime(end_date))
]
if query.interval == "1m":
data_list = r.json()["data"]
date: list[datetime] = []
open_: list[float] = []
high: list[float] = []
low: list[float] = []
close: list[float] = []
volume: list[float] = []
calls_volume: list[float] = []
puts_volume: list[float] = []
total_options_volume: list[float] = []
for data in data_list:
date.append(data["datetime"])
open_.append(data["price"]["open"])
high.append(data["price"]["high"])
low.append(data["price"]["low"])
close.append(data["price"]["close"])
volume.append(data["volume"]["stock_volume"])
calls_volume.append(data["volume"]["calls_volume"])
puts_volume.append(data["volume"]["puts_volume"])
total_options_volume.append(data["volume"]["total_options_volume"])
data = pd.DataFrame()
date = [d.replace("T", " ") for d in date]
date = [datetime.strptime(d, "%Y-%m-%d %H:%M:%S") for d in date]
data["date"] = date
data["open"] = open_
data["high"] = high
data["low"] = low
data["close"] = close
data["volume"] = volume
data["calls_volume"] = calls_volume
data["puts_volume"] = puts_volume
data["total_options_volume"] = total_options_volume
data = data.set_index("date").sort_index()
data.index = data.index.strftime("%Y-%m-%d %H:%M:%S")
data = data[data["open"] > 0]
data["volume"] = round(data["volume"].astype("int64"))
data["symbol"] = symbol
return data.drop_duplicates().reset_index()
for ticker in tickers:
if ticker != "NDX":
data = get_one(
ticker,
start_date=query.start_date,
end_date=query.end_date,
interval=query.interval,
).set_index(["date", "symbol"])
multi = pd.concat([multi, data], axis=0)
multi = multi.sort_index().reset_index()
if len(tickers) == 1:
multi = multi.drop(columns=["symbol"])
return multi.to_dict("records")
urls = [
_generate_historical_prices_url(symbol, INTERVAL_DICT[query.interval])
for symbol in symbols
]
return await amake_requests(urls, **kwargs)
@staticmethod
def transform_data(
query: CboeEquityHistoricalQueryParams, data: List[Dict], **kwargs: Any
) -> List[CboeEquityHistoricalData]:
"""Transform the data to the standard format."""
return [CboeEquityHistoricalData.model_validate(d) for d in data]
if not data:
raise EmptyDataError()
results = DataFrame()
# Results will be different depending on the interval.
# We will also parse the output from multiple symbols.
for item in data:
result = DataFrame()
_symbol = item["symbol"]
_temp = item["data"]
if query.interval == "1d":
result = DataFrame(_temp)
result["symbol"] = _symbol.replace("_", "").replace("^", "")
result = result.set_index("date")
results = concat([results, result])
if query.interval == "1m":
_datetime = Series([d["datetime"] for d in _temp]).rename("date")
_price = DataFrame(d["price"] for d in _temp)
_volume = DataFrame(d["volume"] for d in _temp)
result = _price.join([_volume, _datetime])
result["symbol"] = _symbol.replace("_", "").replace("^", "")
result = result.set_index("date")
results = concat([results, result])
results = results.set_index("symbol", append=True).sort_index()
# There are some bad data points in the open/high/low results that will break things.
for c in results.columns:
# Some symbols do not have volume data, and some intraday symbols don't have options.
if c in ["volume", "puts_volume", "calls_volume", "total_options_volume"]:
results[c] = results[c].astype(float).astype("int64")
results = (
results.drop(columns=c)
if results[c].sum() == 0 and c != "volume"
else results
)
# Sub-penny prices are not warranted for any of the assets returned.
if c in ["open", "high", "low", "close"]:
with contextlib.suppress(Exception):
results[c] = results[c].astype(float)
results[c] = round(results[c], 2)
output = results.dropna(how="all", axis=1).reset_index()
output = output[output["open"] > 0]
# When there is only one ticker symbol, the symbol column is redundant.
if len(query.symbol.split(",")) == 1:
output = output.drop(columns="symbol")
# Finally, we apply the user-specified date range because it is not filtered at the source.
output = output[
(to_datetime(output["date"]) >= to_datetime(query.start_date))
& (
to_datetime(output["date"])
<= to_datetime(query.end_date + timedelta(days=1))
)
]
return [
CboeEquityHistoricalData.model_validate(d)
for d in output.to_dict("records")
]

140
openbb_platform/providers/cboe/openbb_cboe/models/equity_info.py
View File

@@ -1,140 +0,0 @@
"""CBOE Equity Info Model."""
import concurrent.futures
from datetime import datetime
from typing import Any, Dict, List, Optional
import pandas as pd
from openbb_cboe.utils.helpers import (
get_cboe_directory,
get_cboe_index_directory,
get_ticker_info,
get_ticker_iv,
)
from openbb_core.provider.abstract.fetcher import Fetcher
from openbb_core.provider.standard_models.equity_info import (
EquityInfoData,
EquityInfoQueryParams,
)
from pydantic import Field
class CboeEquityInfoQueryParams(EquityInfoQueryParams):
"""CBOE Equity Info Query.
Source: https://www.cboe.com/
"""
class CboeEquityInfoData(EquityInfoData):
"""CBOE Equity Info Data."""
type: Optional[str] = Field(default=None, description="Type of asset.")
exchange_id: Optional[int] = Field(
default=None, description="The Exchange ID number."
)
tick: Optional[str] = Field(
default=None, description="Whether the last sale was an up or down tick."
)
bid: Optional[float] = Field(default=None, description="Current bid price.")
bid_size: Optional[float] = Field(default=None, description="Bid lot size.")
ask: Optional[float] = Field(default=None, description="Current ask price.")
ask_size: Optional[float] = Field(default=None, description="Ask lot size.")
volume: Optional[float] = Field(
default=None, description="Stock volume for the current trading day."
)
iv30: Optional[float] = Field(
default=None, description="The 30-day implied volatility of the stock."
)
iv30_change: Optional[float] = Field(
default=None, description="Change in 30-day implied volatility of the stock."
)
last_trade_timestamp: Optional[datetime] = Field(
default=None, description="Last trade timestamp for the stock."
)
iv30_annual_high: Optional[float] = Field(
default=None, description="The 1-year high of implied volatility."
)
hv30_annual_high: Optional[float] = Field(
default=None, description="The 1-year high of realized volatility."
)
iv30_annual_low: Optional[float] = Field(
default=None, description="The 1-year low of implied volatility."
)
hv30_annual_low: Optional[float] = Field(
default=None, description="The 1-year low of realized volatility."
)
iv60_annual_high: Optional[float] = Field(
default=None, description="The 60-day high of implied volatility."
)
hv60_annual_high: Optional[float] = Field(
default=None, description="The 60-day high of realized volatility."
)
iv60_annual_low: Optional[float] = Field(
default=None, description="The 60-day low of implied volatility."
)
hv60_annual_low: Optional[float] = Field(
default=None, description="The 60-day low of realized volatility."
)
iv90_annual_high: Optional[float] = Field(
default=None, description="The 90-day high of implied volatility."
)
hv90_annual_high: Optional[float] = Field(
default=None, description="The 90-day high of realized volatility."
)
class CboeEquityInfoFetcher(
Fetcher[
CboeEquityInfoQueryParams,
List[CboeEquityInfoData],
]
):
"""Transform the query, extract and transform the data from the CBOE endpoints."""
@staticmethod
def transform_query(params: Dict[str, Any]) -> CboeEquityInfoQueryParams:
"""Transform the query."""
return CboeEquityInfoQueryParams(**params)
@staticmethod
def extract_data(
query: CboeEquityInfoQueryParams, # pylint: disable=unused-argument
credentials: Optional[Dict[str, str]],
**kwargs: Any,
) -> List[Dict]:
"""Return the raw data from the CBOE endpoint."""
results = []
INDEXES = get_cboe_index_directory().index.to_list()
SYMBOLS = get_cboe_directory()
def get_one(symbol):
data = pd.Series(dtype="object")
if symbol in SYMBOLS.index or symbol in INDEXES:
_info = pd.Series(get_ticker_info(symbol))
_iv = pd.Series(get_ticker_iv(symbol))
data = (
pd.DataFrame(pd.concat([_info, _iv]))
.transpose()
.drop(columns="seqno")
.iloc[0]
)
results.append(data.to_dict())
with concurrent.futures.ThreadPoolExecutor() as executor:
executor.map(get_one, query.symbol.split(","))
return (
pd.DataFrame.from_records(results)
.sort_values(by="symbol")
.to_dict("records")
)
@staticmethod
def transform_data(
query: CboeEquityInfoQueryParams, data: List[Dict], **kwargs: Any
) -> List[CboeEquityInfoData]:
"""Transform the data to the standard format."""
return [CboeEquityInfoData.model_validate(d) for d in data]

244
openbb_platform/providers/cboe/openbb_cboe/models/equity_quote.py Normal file
View File

@@ -0,0 +1,244 @@
"""Cboe Equity Info Model."""
# pylint: disable=invalid-name,too-many-locals, expression-not-assigned
from typing import Any, Dict, List, Optional
from openbb_cboe.utils.helpers import (
TICKER_EXCEPTIONS,
get_company_directory,
get_index_directory,
)
from openbb_core.provider.abstract.fetcher import Fetcher
from openbb_core.provider.standard_models.equity_quote import (
EquityQuoteData,
EquityQuoteQueryParams,
)
from openbb_core.provider.utils.errors import EmptyDataError
from openbb_core.provider.utils.helpers import amake_requests
from pandas import DataFrame, concat
from pydantic import Field
class CboeEquityQuoteQueryParams(EquityQuoteQueryParams):
"""CBOE Equity Quote Query.
Source: https://www.cboe.com/
"""
use_cache: bool = Field(
default=True,
description="When True, the company directories will be cached for"
+ " 24 hours and are used to validate symbols."
+ " The results of the function are not cached. Set as False to bypass.",
)
class CboeEquityQuoteData(EquityQuoteData):
"""CBOE Equity Quote Data."""
__alias_dict__ = {
"last_timestamp": "last_trade_time",
"prev_close": "prev_day_close",
"asset_type": "security_type",
"last_price": "current_price",
"year_high": "annual_high",
"year_low": "annual_low",
"last_tick": "tick",
"change": "price_change",
"change_percent": "price_change_percent",
}
iv30: Optional[float] = Field(
default=None, description="The 30-day implied volatility of the stock."
)
iv30_change: Optional[float] = Field(
default=None, description="Change in 30-day implied volatility of the stock."
)
iv30_change_percent: Optional[float] = Field(
default=None,
description="Change in 30-day implied volatility of the"
+ " stock as a normalized percentage value.",
)
iv30_annual_high: Optional[float] = Field(
default=None, description="The 1-year high of 30-day implied volatility."
)
hv30_annual_high: Optional[float] = Field(
default=None, description="The 1-year high of 30-day realized volatility."
)
iv30_annual_low: Optional[float] = Field(
default=None, description="The 1-year low of 30-day implied volatility."
)
hv30_annual_low: Optional[float] = Field(
default=None, description="The 1-year low of 30-dayrealized volatility."
)
iv60_annual_high: Optional[float] = Field(
default=None, description="The 1-year high of 60-day implied volatility."
)
hv60_annual_high: Optional[float] = Field(
default=None, description="The 1-year high of 60-day realized volatility."
)
iv60_annual_low: Optional[float] = Field(
default=None, description="The 1-year low of 60-day implied volatility."
)
hv60_annual_low: Optional[float] = Field(
default=None, description="The 1-year low of 60-day realized volatility."
)
iv90_annual_high: Optional[float] = Field(
default=None, description="The 1-year high of 90-day implied volatility."
)
hv90_annual_high: Optional[float] = Field(
default=None, description="The 1-year high of 90-day realized volatility."
)
iv90_annual_low: Optional[float] = Field(
default=None, description="The 1-year low of 90-day implied volatility."
)
hv90_annual_low: Optional[float] = Field(
default=None, description="The 1-year low of 90-day realized volatility."
)
class CboeEquityQuoteFetcher(
Fetcher[
CboeEquityQuoteQueryParams,
List[CboeEquityQuoteData],
]
):
"""Transform the query, extract and transform the data from the CBOE endpoints."""
@staticmethod
def transform_query(params: Dict[str, Any]) -> CboeEquityQuoteQueryParams:
"""Transform the query."""
return CboeEquityQuoteQueryParams(**params)
@staticmethod
async def aextract_data(
query: CboeEquityQuoteQueryParams, # pylint: disable=unused-argument
credentials: Optional[Dict[str, str]],
**kwargs: Any,
) -> DataFrame:
"""Return the raw data from the Cboe endpoint."""
symbols = query.symbol.split(",")
# First get the index and company directories so we know how to handle the ticker symbols.
# Using cache for faster response times.
SYMBOLS = await get_company_directory(use_cache=query.use_cache, **kwargs)
INDEXES = await get_index_directory(use_cache=query.use_cache, **kwargs)
INDEXES = INDEXES.set_index("index_symbol")
# Create a list of European indices.
EU_INDEXES = INDEXES[INDEXES["source"] == "eu_proprietary_index"]
# Check all symbols and create a list of URLs to request.
urls = []
for symbol in symbols:
base_url = "https://cdn.cboe.com/api/global/delayed_quotes/quotes/"
url = (
f"{base_url}_{symbol.replace('^', '')}.json"
if symbol.replace("^", "") in INDEXES.index
or symbol.replace("^", "") in TICKER_EXCEPTIONS
else f"{base_url}{symbol.replace('^', '')}.json"
)
# European Indices require a different endpoint.
if symbol in EU_INDEXES.index:
eu_name = EU_INDEXES.at[symbol, "name"]
_symbol = EU_INDEXES[EU_INDEXES["name"].str.contains(eu_name)].index[0]
url = (
"https://cdn.cboe.com/api/global/european_indices/"
+ f"index_quotes/{_symbol.replace('^', '')}.json"
)
urls.append(url)
# Now make the requests.
responses = await amake_requests(urls)
if not responses:
raise EmptyDataError()
quotes_data = [d["data"] for d in responses]
# There is no context for this data so we'll remove it.
[d.pop("seqno") for d in quotes_data if "seqno" in d]
[d.pop("exchange_id") for d in quotes_data if "exchange_id" in d]
quotes = DataFrame(quotes_data)
quotes.symbol = quotes.symbol.str.replace("^", "")
quotes.symbol = [s.split("-")[0] for s in quotes.symbol]
# Drop an additional symbol column from EU Indices.
if "index" in quotes.columns:
quotes = quotes.drop(columns="index")
quotes = DataFrame(quotes).set_index("symbol")
# Now get the URLs for the IV data.
base_url = "https://cdn.cboe.com/api/global/delayed_quotes/historical_data/"
iv_urls = []
for symbol in symbols:
iv_url = (
base_url + f"_{symbol.replace('^', '')}.json"
if symbol.replace("^", "") in TICKER_EXCEPTIONS
or symbol.replace("^", "") in INDEXES.index
else base_url + f"{symbol.replace('^', '')}.json"
)
# There is no IV data for the EU Indices, so we'll skip those symbols.
if symbol not in EU_INDEXES.index:
iv_urls.append(iv_url)
# While iterating through the symbols, grab the name belonging to the ticker.
if symbol.replace("^", "") in SYMBOLS.index:
quotes.loc[symbol.replace("^", ""), "name"] = SYMBOLS.loc[
symbol.replace("^", ""), "name"
]
if symbol.replace("^", "") in INDEXES.index:
quotes.loc[symbol.replace("^", ""), "name"] = INDEXES.loc[
symbol.replace("^", ""), "name"
]
if symbol.replace("^", "") in EU_INDEXES.index:
quotes.loc[symbol.replace("^", ""), "name"] = EU_INDEXES.loc[
symbol.replace("^", ""), "name"
]
# Now get the IV data.
iv = DataFrame()
iv_responses = await amake_requests(iv_urls)
if iv_responses:
iv_data = [d["data"] for d in iv_responses]
iv = DataFrame(iv_data)
iv["symbol"] = iv["symbol"].astype(str).str.replace("^", "")
iv = iv.set_index("symbol")
if not iv_responses:
iv = DataFrame()
# Merge the IV data with the quotes data.
results = concat([quotes, iv], axis=1)
if len(results) == 0:
raise EmptyDataError()
return results
@staticmethod
def transform_data(
query: CboeEquityQuoteQueryParams, data: DataFrame, **kwargs: Any
) -> List[CboeEquityQuoteData]:
"""Transform the data to the standard format."""
data = data.replace(0, None).dropna(how="all", axis=1)
# We need to convert the percent columns to normalized values.
percent_cols = [
"price_change_percent",
"iv30",
"iv30_change",
"iv30_change_percent",
"iv30_annual_high",
"iv30_annual_low",
"iv60_annual_high",
"iv60_annual_low",
"iv90_annual_high",
"iv90_annual_low",
"hv30_annual_high",
"hv30_annual_low",
"hv60_annual_high",
"hv60_annual_low",
"hv90_annual_high",
"hv90_annual_low",
]
for col in percent_cols:
if col in data.columns:
data[col] = data[col] / 100
data = data.dropna(how="all", axis=1).fillna("N/A").replace("N/A", None)
return [
CboeEquityQuoteData.model_validate(d)
for d in data.reset_index().to_dict("records")
]

15
openbb_platform/providers/cboe/openbb_cboe/models/equity_search.py
View File

@@ -2,7 +2,7 @@
from typing import Any, Dict, List, Optional
from openbb_cboe.utils.helpers import get_cboe_directory
from openbb_cboe.utils.helpers import get_company_directory
from openbb_core.provider.abstract.fetcher import Fetcher
from openbb_core.provider.standard_models.equity_search import (
EquitySearchData,
@@ -17,12 +17,16 @@ class CboeEquitySearchQueryParams(EquitySearchQueryParams):
Source: https://www.cboe.com/
"""
use_cache: bool = Field(
default=True,
description="When True, the company directory of optionable tickers will be cached for 24 hours."
+ " Set as False to bypass.",
)
class CboeEquitySearchData(EquitySearchData):
"""CBOE Equity Search Data."""
__alias_dict__ = {"name": "Company Name"}
dpm_name: Optional[str] = Field(
default=None,
description="Name of the primary market maker.",
@@ -47,14 +51,15 @@ class CboeEquitySearchFetcher(
return CboeEquitySearchQueryParams(**params)
@staticmethod
def extract_data( # pylint: disable=unused-argument
async def aextract_data(
query: CboeEquitySearchQueryParams,
credentials: Optional[Dict[str, str]],
**kwargs: Any,
) -> Dict:
"""Return the raw data from the CBOE endpoint."""
data = {}
symbols = get_cboe_directory().reset_index().replace("nan", None)
symbols = await get_company_directory(query.use_cache, **kwargs)
symbols = symbols.reset_index()
target = "name" if query.is_symbol is False else "symbol"
idx = symbols[target].str.contains(query.query, case=False)
result = symbols[idx].to_dict("records")

116
openbb_platform/providers/cboe/openbb_cboe/models/european_index_constituents.py
View File

@@ -1,116 +0,0 @@
"""CBOE European Index Constituents Model."""
from datetime import datetime
from typing import Any, Dict, List, Optional
import pandas as pd
from openbb_cboe.utils.helpers import EUR_INDEX_CONSTITUENTS_COLUMNS, Europe
from openbb_core.provider.abstract.fetcher import Fetcher
from openbb_core.provider.standard_models.european_index_constituents import (
EuropeanIndexConstituentsData,
EuropeanIndexConstituentsQueryParams,
)
from openbb_core.provider.utils.helpers import make_request
from pydantic import Field, field_validator
class CboeEuropeanIndexConstituentsQueryParams(EuropeanIndexConstituentsQueryParams):
"""CBOE European Index Constituents Query.
Source: https://www.cboe.com/
Gets the current price data for all constituents of the CBOE European Index.
"""
class CboeEuropeanIndexConstituentsData(EuropeanIndexConstituentsData):
"""CBOE European Index Constituents Data.
Current trading day price data for all constituents of the CBOE European Index.
"""
prev_close: Optional[float] = Field(
default=None, description="Previous closing price."
)
change: Optional[float] = Field(default=None, description="Change in price.")
change_percent: Optional[float] = Field(
default=None, description="Change in price as a percentage."
)
tick: Optional[str] = Field(
default=None, description="Whether the last sale was an up or down tick."
)
last_trade_timestamp: Optional[datetime] = Field(
default=None, description="Last trade timestamp for the symbol."
)
exchange_id: Optional[int] = Field(
default=None, description="The Exchange ID number."
)
seqno: Optional[int] = Field(
default=None, description="Sequence number of the last trade on the tape."
)
asset_type: Optional[str] = Field(
default=None, description="Type of asset.", alias="type"
)
@field_validator("last_trade_timestamp", mode="before", check_fields=False)
def date_validate(cls, v): # pylint: disable=E0213
"""Return the datetime object from the date string."""
return datetime.strftime(v, "%Y-%m-%d %H:%M:%S")
class CboeEuropeanIndexConstituentsFetcher(
Fetcher[
CboeEuropeanIndexConstituentsQueryParams,
List[CboeEuropeanIndexConstituentsData],
]
):
"""Transform the query, extract and transform the data from the CBOE endpoints."""
@staticmethod
def transform_query(
params: Dict[str, Any]
) -> CboeEuropeanIndexConstituentsQueryParams:
"""Transform the query."""
return CboeEuropeanIndexConstituentsQueryParams(**params)
@staticmethod
def extract_data(
query: CboeEuropeanIndexConstituentsQueryParams,
credentials: Optional[Dict[str, str]],
**kwargs: Any,
) -> List[Dict]:
"""Return the raw data from the CBOE endpoint."""
SYMBOLS = pd.DataFrame(Europe.list_indices())["symbol"].to_list()
query.symbol = query.symbol.upper()
if query.symbol not in SYMBOLS:
raise RuntimeError(
f"The symbol, {query.symbol},"
"was not found in the CBOE European Index directory. "
"Use `available_indices(europe=True)` to see the full list of indices."
)
url = f"https://cdn.cboe.com/api/global/european_indices/constituent_quotes/{query.symbol}.json"
r = make_request(url)
if r.status_code != 200:
raise RuntimeError(r.status_code)
r_json = r.json()
data = (
pd.DataFrame.from_records(r_json["data"])[
list(EUR_INDEX_CONSTITUENTS_COLUMNS.keys())
]
.rename(columns=EUR_INDEX_CONSTITUENTS_COLUMNS)
.round(2)
)
data["last_trade_timestamp"] = pd.to_datetime(data["last_trade_timestamp"])
return data.to_dict("records")
@staticmethod
def transform_data(
query: CboeEuropeanIndexConstituentsQueryParams, data: List[Dict], **kwargs: Any
) -> List[CboeEuropeanIndexConstituentsData]:
"""Transform the data to the standard format."""
return [CboeEuropeanIndexConstituentsData.model_validate(d) for d in data]

142
openbb_platform/providers/cboe/openbb_cboe/models/european_indices.py
View File

@@ -1,142 +0,0 @@
"""CBOE European Indices Model."""
from datetime import datetime
from typing import Any, Dict, List, Literal, Optional
import pandas as pd
from dateutil.relativedelta import relativedelta
from openbb_cboe.utils.helpers import Europe
from openbb_core.provider.abstract.fetcher import Fetcher
from openbb_core.provider.standard_models.european_indices import (
EuropeanIndicesData,
EuropeanIndicesQueryParams,
)
from openbb_core.provider.utils.helpers import make_request
from pydantic import Field, field_validator
class CboeEuropeanIndicesQueryParams(EuropeanIndicesQueryParams):
"""CBOE European Indices Query.
Source: https://www.cboe.com/europe/indices/
"""
interval: Literal["1d", "1m"] = Field(description="Data granularity.", default="1d")
class CboeEuropeanIndicesData(EuropeanIndicesData):
"""CBOE European Indices Data."""
open: Optional[float] = Field(
default=None,
description="Opening price for the interval. Only valid when interval is 1m.",
)
high: Optional[float] = Field(
default=None,
description="High price for the interval. Only valid when interval is 1m.",
)
low: Optional[float] = Field(
default=None,
description="Low price for the interval. Only valid when interval is 1m.",
)
utc_datetime: Optional[datetime] = Field(
default=None, description="UTC datetime. Only valid when interval is 1m."
)
@field_validator("date", mode="before", check_fields=False)
def date_validate(cls, v): # pylint: disable=E0213
"""Return datetime object from string."""
try:
return datetime.strptime(v, "%Y-%m-%d")
except Exception:
return datetime.strptime(v, "%Y-%m-%dT%H:%M:%S")
class CboeEuropeanIndicesFetcher(
Fetcher[
CboeEuropeanIndicesQueryParams,
List[CboeEuropeanIndicesData],
]
):
"""Transform the query, extract and transform the data from the CBOE endpoints."""
@staticmethod
def transform_query(params: Dict[str, Any]) -> CboeEuropeanIndicesQueryParams:
"""Transform the query."""
now = datetime.now().date()
transformed_params = params
if params.get("start_date") is None:
transformed_params["start_date"] = now - relativedelta(years=1)
if params.get("end_date") is None:
transformed_params["end_date"] = now
return CboeEuropeanIndicesQueryParams(**transformed_params)
@staticmethod
def extract_data(
query: CboeEuropeanIndicesQueryParams,
credentials: Optional[Dict[str, str]],
**kwargs: Any,
) -> List[Dict]:
"""Return the raw data from the CBOE endpoint."""
data = pd.DataFrame()
query.symbol = query.symbol.upper()
SYMBOLS = pd.DataFrame(Europe.list_indices())["symbol"].to_list()
if query.symbol not in SYMBOLS:
raise RuntimeError(
f"The symbol, {query.symbol},"
"was not found in the CBOE European Indices directory. "
"Use `available_indices(europe=True)` to see the full list of indices."
)
if query.interval == "1d":
url = f"https://cdn.cboe.com/api/global/european_indices/index_history/{query.symbol}.json"
r = make_request(url)
if r.status_code != 200:
raise RuntimeError(r.status_code)
r_json = r.json()
data = pd.DataFrame.from_records(r_json["data"]).set_index("date")
data.index = pd.to_datetime(data.index, format="%Y-%m-%d")
if query.start_date is not None:
query.end_date = (
query.end_date if query.end_date else datetime.now().date()
)
data = data[
(data.index >= pd.to_datetime(query.start_date, format="%Y-%m-%d"))
& (data.index <= pd.to_datetime(query.end_date, format="%Y-%m-%d"))
]
data.index = data.index.astype(str)
data = data.reset_index()
if query.interval == "1m":
url = f"https://cdn.cboe.com/api/global/european_indices/intraday_chart_data/{query.symbol}.json"
r = make_request(url)
if r.status_code != 200:
raise RuntimeError(r.status_code)
r_json = r.json()["data"]
data = pd.DataFrame.from_records(pd.DataFrame(r_json)["price"])
data["date"] = pd.DataFrame(r_json)["datetime"]
data["utc_datetime"] = pd.to_datetime(pd.DataFrame(r_json)["utc_datetime"])
data = data[["utc_datetime", "date", "open", "high", "low", "close"]].round(
2
)
return data.to_dict("records")
@staticmethod
def transform_data(
query: CboeEuropeanIndicesQueryParams, data: List[Dict], **kwargs: Any
) -> List[CboeEuropeanIndicesData]:
"""Transform the data to the standard format."""
return [CboeEuropeanIndicesData.model_validate(d) for d in data]

19
openbb_platform/providers/cboe/openbb_cboe/models/futures_curve.py
View File

@@ -9,6 +9,7 @@ from openbb_core.provider.standard_models.futures_curve import (
FuturesCurveData,
FuturesCurveQueryParams,
)
from openbb_core.provider.utils.errors import EmptyDataError
from pydantic import Field
@@ -38,30 +39,28 @@ class CboeFuturesCurveFetcher(
return CboeFuturesCurveQueryParams(**params)
@staticmethod
def extract_data(
async def aextract_data(
query: CboeFuturesCurveQueryParams,
credentials: Optional[Dict[str, str]],
**kwargs: Any,
) -> List[Dict]:
"""Return the raw data from the CBOE endpoint."""
query.symbol = query.symbol.upper()
FUTURES = get_settlement_prices(settlement_date=query.date)
symbol = query.symbol.upper().split(",")[0]
FUTURES = await get_settlement_prices(**kwargs)
if len(FUTURES) == 0:
return []
raise EmptyDataError()
if query.symbol not in FUTURES["product"].unique().tolist():
if symbol not in FUTURES["product"].unique().tolist():
raise RuntimeError(
"The symbol, "
f"{query.symbol}"
f"{symbol}"
", is not valid. Chose from: "
f"{FUTURES['product'].unique().tolist()}"
)
data = FUTURES[FUTURES["product"] == symbol][["expiration", "symbol", "price"]]
data = get_settlement_prices(settlement_date=query.date)
data = data[data["product"] == query.symbol]
return data[["expiration", "symbol", "price"]].to_dict("records")
return data.to_dict("records")
@staticmethod
def transform_data(

130
openbb_platform/providers/cboe/openbb_cboe/models/index_constituents.py Normal file
View File

@@ -0,0 +1,130 @@
"""Cboe Index Constituents Model."""
# pylint: disable=unused-argument
from datetime import datetime
from typing import Any, Dict, List, Optional
from openbb_cboe.utils.helpers import CONSTITUENTS_EU
from openbb_core.provider.abstract.fetcher import Fetcher
from openbb_core.provider.standard_models.index_constituents import (
IndexConstituentsData,
IndexConstituentsQueryParams,
)
from openbb_core.provider.utils.descriptions import DATA_DESCRIPTIONS
from openbb_core.provider.utils.errors import EmptyDataError
from openbb_core.provider.utils.helpers import amake_request
from pandas import DataFrame
from pydantic import Field, field_validator
class CboeIndexConstituentsQueryParams(IndexConstituentsQueryParams):
"""Cboe Index Constituents Query.
Source: https://www.cboe.com/
Gets the current price data for all constituents of the CBOE European Index.
"""
index: CONSTITUENTS_EU = Field(default="BUK100P")
class CboeIndexConstituentsData(IndexConstituentsData):
"""Cboe Index Constituents Data.
Current trading day price data for all constituents of the Cboe proprietary index.
"""
__alias_dict__ = {
"prev_close": "prev_day_close",
"change": "price_change",
"change_percent": "price_change_percent",
"last_price": "current_price",
}
security_type: Optional[str] = Field(
default=None, description="The type of security represented."
)
last_price: Optional[float] = Field(
default=None, description="Last price for the symbol."
)
open: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("open", "")
)
high: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("high", "")
)
low: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("low", "")
)
close: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("close", "")
)
volume: Optional[int] = Field(
default=None, description=DATA_DESCRIPTIONS.get("volume", "")
)
prev_close: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("prev_close", "")
)
change: Optional[float] = Field(default=None, description="Change in price.")
change_percent: Optional[float] = Field(
default=None, description="Change in price as a normalized percentage."
)
tick: Optional[str] = Field(
default=None, description="Whether the last sale was an up or down tick."
)
last_trade_time: Optional[datetime] = Field(
default=None, description="Last trade timestamp for the symbol."
)
asset_type: Optional[str] = Field(
default=None, description="Type of asset.", alias="type"
)
@field_validator("last_trade_time", mode="before", check_fields=False)
@classmethod
def date_validate(cls, v): # pylint: disable=E0213
"""Return the datetime object from the date string."""
return datetime.strptime(v, "%Y-%m-%dT%H:%M:%S")
class CboeIndexConstituentsFetcher(
Fetcher[
CboeIndexConstituentsQueryParams,
List[CboeIndexConstituentsData],
]
):
"""Transform the query, extract and transform the data from the CBOE endpoints."""
@staticmethod
def transform_query(params: Dict[str, Any]) -> CboeIndexConstituentsQueryParams:
"""Transform the query."""
return CboeIndexConstituentsQueryParams(**params)
@staticmethod
async def aextract_data(
query: CboeIndexConstituentsQueryParams,
credentials: Optional[Dict[str, str]],
**kwargs: Any,
) -> List[Dict]:
"""Return the raw data from the Cboe endpoint."""
url = (
"https://cdn.cboe.com/api/global/european_indices"
f"/constituent_quotes/{query.index}.json"
)
data = await amake_request(url)
return data.get("data")
@staticmethod
def transform_data(
query: CboeIndexConstituentsQueryParams, data: List[Dict], **kwargs: Any
) -> List[CboeIndexConstituentsData]:
"""Transform the data to the standard format."""
if not data:
raise EmptyDataError()
data = DataFrame(data)
data["price_change_percent"] = data["price_change_percent"] / 100
data = data.replace(0, None).dropna(how="all", axis=1)
data = data.drop(columns=["exchange_id"])
return [
CboeIndexConstituentsData.model_validate(d)
for d in data.to_dict(orient="records")
]

282
openbb_platform/providers/cboe/openbb_cboe/models/index_historical.py
View File

@@ -1,37 +1,54 @@
"""CBOE Index Historical Model."""
"""Cboe Market Indices Model."""
import warnings
from datetime import datetime, timedelta
from typing import Any, Dict, List, Literal, Optional
import pandas as pd
from openbb_cboe.utils.helpers import (
TICKER_EXCEPTIONS,
get_cboe_index_directory,
get_ticker_info,
get_index_directory,
)
from openbb_core.provider.abstract.fetcher import Fetcher
from openbb_core.provider.standard_models.index_historical import (
IndexHistoricalData,
IndexHistoricalQueryParams,
)
from openbb_core.provider.utils.helpers import make_request
from openbb_core.provider.utils.descriptions import QUERY_DESCRIPTIONS
from openbb_core.provider.utils.errors import EmptyDataError
from openbb_core.provider.utils.helpers import amake_requests
from pandas import DataFrame, Series, concat, to_datetime
from pydantic import Field
_warn = warnings.warn
class CboeIndexHistoricalQueryParams(IndexHistoricalQueryParams):
"""CBOE Index Historical Query.
"""CBOE Market Indices Query.
Source: https://www.cboe.com/
"""
interval: Literal["1d", "1m"] = Field(
description="Use interval, 1m, for intraday prices during the most recent trading period.",
interval: Literal["1m", "1d"] = Field(
default="1d",
description=(
QUERY_DESCRIPTIONS.get("interval", "")
+ " The most recent trading day is not including in daily historical data."
+ " Intraday data is only available for the most recent trading day at 1 minute intervals."
),
)
use_cache: bool = Field(
default=True,
description="When True, the company directories will be cached for 24 hours and are used to validate symbols."
+ " The results of the function are not cached. Set as False to bypass.",
)
class CboeIndexHistoricalData(IndexHistoricalData):
"""CBOE Index Historical Data."""
"""CBOE Market Indices Data."""
__alias_dict__ = {
"volume": "stock_volume",
}
calls_volume: Optional[float] = Field(
default=None,
@@ -57,156 +74,135 @@ class CboeIndexHistoricalFetcher(
@staticmethod
def transform_query(params: Dict[str, Any]) -> CboeIndexHistoricalQueryParams:
"""Transform the query. Setting the start and end dates for a 1 year period."""
return CboeIndexHistoricalQueryParams(**params)
"""Transform the query."""
transformed_params = params.copy()
now = datetime.now()
if (
len(params.get("symbol", "").split(",")) > 1
and params.get("start_date") is None
):
transformed_params["start_date"] = (
transformed_params["start_date"]
if transformed_params["start_date"]
else (now - timedelta(days=720)).strftime("%Y-%m-%d")
)
if transformed_params.get("start_date") is None:
transformed_params["start_date"] = (
transformed_params["start_date"]
if transformed_params.get("start_date")
else "1950-01-01"
)
if params.get("end_date") is None:
transformed_params["end_date"] = (
transformed_params["end_date"]
if transformed_params.get("end_date")
else now.strftime("%Y-%m-%d")
)
return CboeIndexHistoricalQueryParams(**transformed_params)
@staticmethod
def extract_data(
query: CboeIndexHistoricalQueryParams, # pylint: disable=unused-argument
async def aextract_data(
query: CboeIndexHistoricalQueryParams,
credentials: Optional[Dict[str, str]],
**kwargs: Any,
) -> List[Dict]:
"""Return the raw data from the CBOE endpoint."""
# Symbol directories are cached for seven days and are used for error handling and URL generation.
INDEXES = get_cboe_index_directory().index.to_list()
query.symbol = query.symbol.upper()
data = pd.DataFrame()
if "^" in query.symbol:
query.symbol = query.symbol.replace("^", "")
query.interval = (
"1m" if query.symbol == "NDX" and query.interval == "1d" else query.interval
)
"""Return the raw data from the Cboe endpoint."""
now = datetime.now()
query.start_date = (
query.start_date if query.start_date else now - timedelta(days=50000)
)
query.end_date = query.end_date if query.end_date else now
symbols = query.symbol.split(",")
INDEXES = await get_index_directory(use_cache=query.use_cache)
INDEXES = INDEXES.set_index("index_symbol")
# Create a list of European indices.
EU_INDEXES = INDEXES[INDEXES["source"] == "eu_proprietary_index"]
if query.symbol not in INDEXES and query.symbol not in TICKER_EXCEPTIONS:
raise RuntimeError(
f"The symbol, {query.symbol}, was not found in the CBOE index directory. "
"Use `index_search()` to find supported indices. If the index is European, try `european_index()`."
)
INTERVAL_DICT = {"1m": "intraday", "1d": "historical"}
def __generate_historical_prices_url(
def _generate_historical_prices_url(
symbol,
data_type: Optional[Literal["intraday", "historical"]] = "historical",
interval_type: Literal["intraday", "historical"] = "historical",
) -> str:
"""Generate the final URL for historical prices data."""
url: str = (
f"https://cdn.cboe.com/api/global/delayed_quotes/charts/{data_type}"
)
url = (
url + f"/_{symbol}.json"
if symbol in TICKER_EXCEPTIONS or symbol in INDEXES
else url + f"/{symbol}.json"
)
"""Generate the URL for the data."""
if symbol.replace("^", "") in TICKER_EXCEPTIONS:
interval_type = "intraday" if len(symbols) == 1 else "historical"
_warn(
"Only the most recent trading day is available for this ticker, "
+ symbol
)
if symbol.replace("^", "") in EU_INDEXES.index:
base_url = "https://cdn.cboe.com/api/global/european_indices/"
url = (
base_url + "index_history/"
if interval_type == "historical"
else base_url + "intraday_chart_data/"
)
url += f"{symbol.replace('^', '')}.json"
else:
base_url: str = f"https://cdn.cboe.com/api/global/delayed_quotes/charts/{interval_type}"
url = (
base_url + f"/_{symbol.replace('^', '')}.json"
if symbol.replace("^", "") in TICKER_EXCEPTIONS
or symbol.replace("^", "") in INDEXES.index
else base_url + f"/{symbol.replace('^', '')}.json"
)
return url
url = (
__generate_historical_prices_url(query.symbol, "intraday")
if query.interval == "1m"
else __generate_historical_prices_url(query.symbol)
)
r = make_request(url)
urls = [
_generate_historical_prices_url(symbol, INTERVAL_DICT[query.interval])
for symbol in symbols
]
if r.status_code != 200:
raise RuntimeError(r.status_code)
if query.interval == "1d":
data = (
pd.DataFrame(r.json()["data"])[
["date", "open", "high", "low", "close", "volume"]
]
).set_index("date")
# Fill in missing data from current or most recent trading session.
today = pd.to_datetime(datetime.now().date())
if today.weekday() > 4:
day_minus = today.weekday() - 4
today = pd.to_datetime(today - timedelta(days=day_minus))
if today != data.index[-1]:
_today = pd.Series(get_ticker_info(query.symbol))
today_df = pd.Series(dtype="object")
today_df["open"] = round(_today["open"], 2)
today_df["high"] = round(_today["high"], 2)
today_df["low"] = round(_today["low"], 2)
today_df["close"] = round(_today["close"], 2)
if (
query.symbol not in INDEXES
and query.symbol not in TICKER_EXCEPTIONS
):
data = data[data["volume"] > 0]
today_df["volume"] = _today["volume"]
today_df["date"] = today.date()
today_df = pd.DataFrame(today_df).transpose().set_index("date")
data = pd.concat([data, today_df], axis=0)
# If ticker is an index there is no volume data and the types must be set.
if query.symbol in INDEXES or query.symbol in TICKER_EXCEPTIONS:
data = data[["open", "high", "low", "close", "volume"]]
data["open"] = round(data.open.astype(float), 2)
data["high"] = round(data.high.astype(float), 2)
data["low"] = round(data.low.astype(float), 2)
data["close"] = round(data.close.astype(float), 2)
data["volume"] = 0
data.index = pd.to_datetime(data.index)
data = data[data["open"] > 0]
data = data[
(data.index >= pd.to_datetime(query.start_date))
& (data.index <= pd.to_datetime(query.end_date))
]
if query.interval == "1m":
data_list = r.json()["data"]
date: List[datetime] = []
open_: List[float] = []
high: List[float] = []
low: List[float] = []
close: List[float] = []
volume: List[float] = []
calls_volume: List[float] = []
puts_volume: List[float] = []
total_options_volume: List[float] = []
for data in data_list:
date.append(data["datetime"])
price = data["price"]
volume_data = data["volume"]
open_.append(price["open"])
high.append(price["high"])
low.append(price["low"])
close.append(price["close"])
volume.append(volume_data["stock_volume"])
calls_volume.append(volume_data["calls_volume"])
puts_volume.append(volume_data["puts_volume"])
total_options_volume.append(volume_data["total_options_volume"])
data = pd.DataFrame()
data["date"] = pd.to_datetime(date)
data["open"] = open_
data["high"] = high
data["low"] = low
data["close"] = close
data["volume"] = volume
data["calls_volume"] = calls_volume
data["puts_volume"] = puts_volume
data["total_options_volume"] = total_options_volume
data = data.set_index("date").sort_index()
data.index = data.index.astype(str)
data = data[data["open"] > 0]
return data.reset_index().to_dict("records")
return await amake_requests(urls, **kwargs)
@staticmethod
def transform_data(
query: CboeIndexHistoricalQueryParams, data: List[Dict], **kwargs: Any
) -> List[CboeIndexHistoricalData]:
"""Transform the data to the standard format."""
return [CboeIndexHistoricalData.model_validate(d) for d in data]
if not data:
raise EmptyDataError()
results = DataFrame()
symbols = query.symbol.split(",")
# Results will be different depending on the interval.
# We will also parse the output from multiple symbols.
for i, item in enumerate(data):
result = DataFrame()
_symbol = symbols[i]
_temp = item["data"]
if query.interval == "1d":
result = DataFrame(_temp)
result["symbol"] = _symbol.replace("_", "").replace("^", "")
result = result.set_index("date")
# Remove the volume column if it exists because volume will a string 0.
if "volume" in result.columns:
result = result.drop(columns="volume")
results = concat([results, result])
if query.interval == "1m":
_datetime = Series([d["datetime"] for d in _temp]).rename("date")
_price = DataFrame(d["price"] for d in _temp)
result = _price.join(_datetime)
result["symbol"] = _symbol.replace("_", "").replace("^", "")
result = result.set_index("date")
results = concat([results, result])
results = results.set_index("symbol", append=True).sort_index()
for c in ["open", "high", "low", "close"]:
if c in results.columns:
results[c] = results[c].astype(float).replace(0, None)
output = results.dropna(how="all", axis=1).reset_index()
# When there is only one ticker symbol, the symbol column is redundant.
if len(query.symbol.split(",")) == 1:
output = output.drop(columns="symbol")
# Finally, we apply the user-specified date range because it is not filtered at the source.
output = output[
(to_datetime(output["date"]) >= to_datetime(query.start_date))
& (
to_datetime(output["date"])
<= to_datetime(query.end_date + timedelta(days=1))
)
]
return [
CboeIndexHistoricalData.model_validate(d) for d in output.to_dict("records")
]

46
openbb_platform/providers/cboe/openbb_cboe/models/index_search.py
View File

@@ -3,8 +3,7 @@
from datetime import time
from typing import Any, Dict, List, Optional
import pandas as pd
from openbb_cboe.utils.helpers import Europe, get_cboe_index_directory
from openbb_cboe.utils.helpers import get_index_directory
from openbb_core.provider.abstract.fetcher import Fetcher
from openbb_core.provider.standard_models.index_search import (
IndexSearchData,
@@ -19,22 +18,23 @@ class CboeIndexSearchQueryParams(IndexSearchQueryParams):
Source: https://www.cboe.com/
"""
europe: bool = Field(
description="Filter for European indices. False for US indices.", default=False
use_cache: bool = Field(
default=True,
description="When True, the Cboe Index directory will be cached for 24 hours."
+ " Set as False to bypass.",
)
class CboeIndexSearchData(IndexSearchData):
"""CBOE Index Search Data."""
isin: Optional[str] = Field(
description="ISIN code for the index. Valid only for European indices.",
default=None,
)
region: Optional[str] = Field(
description="Region for the index. Valid only for European indices",
default=None,
)
__alias_dict__ = {
"symbol": "index_symbol",
"data_delay": "mkt_data_delay",
"open_time": "calc_start_time",
"close_time": "calc_end_time",
}
description: Optional[str] = Field(
description="Description for the index.", default=None
)
@@ -81,21 +81,25 @@ class CboeIndexSearchFetcher(
return CboeIndexSearchQueryParams(**params)
@staticmethod
def extract_data(
async def aextract_data(
query: CboeIndexSearchQueryParams,
credentials: Optional[Dict[str, str]],
**kwargs: Any,
) -> List[Dict]:
"""Return the raw data from the CBOE endpoint."""
symbols = pd.DataFrame()
if query.europe is True:
symbols = pd.DataFrame(Europe.list_indices())
if query.europe is False:
symbols = get_cboe_index_directory().reset_index()
target = "name" if not query.is_symbol else "symbol"
idx = symbols[target].str.contains(query.query, case=False)
result = symbols[idx]
symbols = await get_index_directory(use_cache=query.use_cache, **kwargs)
symbols.drop(columns=["source"], inplace=True)
if query.is_symbol is True:
result = symbols[
symbols["index_symbol"].str.contains(query.query, case=False)
]
else:
result = symbols[
symbols["name"].str.contains(query.query, case=False)
| symbols["index_symbol"].str.contains(query.query, case=False)
| symbols["description"].str.contains(query.query, case=False)
]
return result.to_dict("records")

182
openbb_platform/providers/cboe/openbb_cboe/models/index_snapshots.py
View File

@@ -1,23 +1,18 @@
"""CBOE Index Snapshots Model."""
from datetime import datetime
from typing import Any, Dict, List, Optional
from typing import Any, Dict, List, Literal, Optional
import pandas as pd
from openbb_cboe.utils.helpers import (
EUR_INDEX_COLUMNS,
US_INDEX_COLUMNS,
Europe,
get_cboe_directory,
get_cboe_index_directory,
)
from openbb_core.provider.abstract.fetcher import Fetcher
from openbb_core.provider.standard_models.index_snapshots import (
IndexSnapshotsData,
IndexSnapshotsQueryParams,
)
from openbb_core.provider.utils.helpers import make_request
from pydantic import Field
from openbb_core.provider.utils.descriptions import DATA_DESCRIPTIONS
from openbb_core.provider.utils.errors import EmptyDataError
from openbb_core.provider.utils.helpers import amake_request
from pandas import DataFrame
from pydantic import Field, field_validator
class CboeIndexSnapshotsQueryParams(IndexSnapshotsQueryParams):
@@ -26,16 +21,55 @@ class CboeIndexSnapshotsQueryParams(IndexSnapshotsQueryParams):
Source: https://www.cboe.com/
"""
region: Literal[None, "us", "eu"] = Field(
default="us",
)
@field_validator("region", mode="after", check_fields=False)
@classmethod
def validate_region(cls, v: str):
"""Validate region."""
return "us" if v is None else v
class CboeIndexSnapshotsData(IndexSnapshotsData):
"""CBOE Index Snapshots Data."""
isin: Optional[str] = Field(
default=None,
description="ISIN code for the index. Valid only for European indices.",
__alias_dict__ = {
"prev_close": "prev_day_close",
"change": "price_change",
"change_percent": "price_change_percent",
"price": "current_price",
}
bid: Optional[float] = Field(default=None, description="Current bid price.")
ask: Optional[float] = Field(default=None, description="Current ask price.")
open: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("open", "")
)
last_trade_timestamp: Optional[datetime] = Field(
default=None, description="Last trade timestamp for the index."
high: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("high", "")
)
low: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("low", "")
)
close: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("close", "")
)
volume: Optional[int] = Field(
default=None, description=DATA_DESCRIPTIONS.get("volume", "")
)
prev_close: Optional[float] = Field(
default=None, description=DATA_DESCRIPTIONS.get("prev_close", "")
)
change: Optional[float] = Field(default=None, description="Change in price.")
change_percent: Optional[float] = Field(
default=None, description="Change in price as a normalized percentage."
)
last_trade_time: Optional[datetime] = Field(
default=None, description="Last trade timestamp for the symbol."
)
status: Optional[str] = Field(
default=None, description="Status of the market, open or closed."
)
@@ -53,89 +87,57 @@ class CboeIndexSnapshotsFetcher(
return CboeIndexSnapshotsQueryParams(**params)
@staticmethod
def extract_data(
async def aextract_data(
query: CboeIndexSnapshotsQueryParams,
credentials: Optional[Dict[str, str]],
**kwargs: Any,
) -> List[Dict]:
"""Return the raw data from the CBOE endpoint"""
data = pd.DataFrame()
"""Return the raw data from the Cboe endpoint"""
if query.region == "US":
r = make_request(
"https://cdn.cboe.com/api/global/delayed_quotes/quotes/all_us_indices.json"
)
if query.region == "us":
url = "https://cdn.cboe.com/api/global/delayed_quotes/quotes/all_us_indices.json"
if query.region == "eu":
url = "https://cdn.cboe.com/api/global/european_indices/index_quotes/all-indices.json"
if r.status_code != 200:
raise RuntimeError(r.status_code)
INDEXES = pd.concat(
[get_cboe_index_directory(), get_cboe_directory()], axis=0
)
data = pd.DataFrame.from_records(r.json()["data"])
data.rename(columns=US_INDEX_COLUMNS, inplace=True)
data["symbol"] = data["symbol"].str.replace("^", "")
data["name"] = ""
data = data.set_index("symbol")
for i in data.index:
if i in INDEXES.index:
data.at[i, "name"] = INDEXES.at[i, "name"]
data["name"] = data["name"].astype(str)
data["currency"] = "USD"
data = data[
[
"name",
"price",
"prev_close",
"change",
"change_percent",
"open",
"high",
"low",
"close",
"currency",
"last_trade_timestamp",
]
]
if query.region == "EU":
r = make_request(
"https://cdn.cboe.com/api/global/european_indices/index_quotes/all-indices.json"
)
if r.status_code != 200:
raise RuntimeError(r.status_code)
data = (
pd.DataFrame.from_records(r.json()["data"])
.drop(columns=["symbol"])
.rename(columns={"index": "symbol"})
.set_index("symbol")
.round(2)
)
INDEXES = pd.DataFrame(Europe.list_indices()).set_index("symbol")
for i in data.index:
data.loc[i, ("isin")] = INDEXES.at[i, "isin"]
data.loc[i, ("name")] = INDEXES.at[i, "name"]
data.loc[i, ("currency")] = INDEXES.at[i, "currency"]
data = data[list(EUR_INDEX_COLUMNS.keys())]
data.columns = list(EUR_INDEX_COLUMNS.values())
data["change_percent"] = data["change_percent"].fillna(0.0)
return data.reset_index().to_dict("records")
data = await amake_request(url, **kwargs)
return data.get("data")
@staticmethod
def transform_data(
query: CboeIndexSnapshotsQueryParams, data: dict, **kwargs: Any
) -> List[CboeIndexSnapshotsData]:
"""Transform the data to the standard format"""
for item in data:
item["name"] = item["name"].replace("/", "-")
return [CboeIndexSnapshotsData.model_validate(d) for d in data]
if not data:
raise EmptyDataError()
data = DataFrame(data)
percent_cols = [
"price_change_percent",
"iv30",
"iv30_change",
"iv30_change_percent",
]
for col in percent_cols:
if col in data.columns:
data[col] = round(data[col] / 100, 6)
data = (
data.replace(0, None)
.replace("", None)
.dropna(how="all", axis=1)
.fillna("N/A")
.replace("N/A", None)
)
drop_cols = [
"exchange_id",
"seqno",
"index",
"security_type",
"ask_size",
"bid_size",
]
for col in drop_cols:
if col in data.columns:
data = data.drop(columns=col)
return [
CboeIndexSnapshotsData.model_validate(d)
for d in data.to_dict(orient="records")
]

211
openbb_platform/providers/cboe/openbb_cboe/models/market_indices.py
View File

@@ -1,211 +0,0 @@
"""CBOE Market Indices Model."""
from datetime import datetime, timedelta
from typing import Any, Dict, List, Literal, Optional
import pandas as pd
from openbb_cboe.utils.helpers import (
TICKER_EXCEPTIONS,
get_cboe_index_directory,
get_ticker_info,
)
from openbb_core.provider.abstract.fetcher import Fetcher
from openbb_core.provider.standard_models.market_indices import (
MarketIndicesData,
MarketIndicesQueryParams,
)
from openbb_core.provider.utils.helpers import make_request
from pydantic import Field
class CboeMarketIndicesQueryParams(MarketIndicesQueryParams):
"""CBOE Market Indices Query.
Source: https://www.cboe.com/
"""
interval: Literal["1d", "1m"] = Field(
description="Use interval, 1m, for intraday prices during the most recent trading period.",
default="1d",
)
class CboeMarketIndicesData(MarketIndicesData):
"""CBOE Market Indices Data."""
calls_volume: Optional[float] = Field(
default=None,
description="Number of calls traded during the most recent trading period. Only valid if interval is 1m.",
)
puts_volume: Optional[float] = Field(
default=None,
description="Number of puts traded during the most recent trading period. Only valid if interval is 1m.",
)
total_options_volume: Optional[float] = Field(
default=None,
description="Total number of options traded during the most recent trading period. Only valid if interval is 1m.",
)
class CboeMarketIndicesFetcher(
Fetcher[
CboeMarketIndicesQueryParams,
List[CboeMarketIndicesData],
]
):
"""Transform the query, extract and transform the data from the CBOE endpoints."""
@staticmethod
def transform_query(params: Dict[str, Any]) -> CboeMarketIndicesQueryParams:
"""Transform the query. Setting the start and end dates for a 1 year period."""
return CboeMarketIndicesQueryParams(**params)
@staticmethod
def extract_data(
query: CboeMarketIndicesQueryParams,
credentials: Optional[Dict[str, str]],
**kwargs: Any,
) -> List[Dict]:
"""Return the raw data from the CBOE endpoint."""
# Synbol directories are cached for seven days and are used for error handling and URL generation.
INDEXES = get_cboe_index_directory().index.to_list()
query.symbol = query.symbol.upper()
data = pd.DataFrame()
if "^" in query.symbol:
query.symbol = query.symbol.replace("^", "")
query.interval = (
"1m" if query.symbol == "NDX" and query.interval == "1d" else query.interval
)
now = datetime.now()
query.start_date = (
query.start_date if query.start_date else now - timedelta(days=50000)
)
query.end_date = query.end_date if query.end_date else now
if query.symbol not in INDEXES and query.symbol not in TICKER_EXCEPTIONS:
raise RuntimeError(
f"The symbol, {query.symbol}, was not found in the CBOE index directory. "
"Use `index_search()` to find supported indices. If the index is European, try `european_index()`."
)
def __generate_historical_prices_url(
symbol,
data_type: Optional[Literal["intraday", "historical"]] = "historical",
) -> str:
"""Generate the final URL for historical prices data."""
url: str = (
f"https://cdn.cboe.com/api/global/delayed_quotes/charts/{data_type}"
)
url = (
url + f"/_{symbol}.json"
if symbol in TICKER_EXCEPTIONS or symbol in INDEXES
else url + f"/{symbol}.json"
)
return url
url = (
__generate_historical_prices_url(query.symbol, "intraday")
if query.interval == "1m"
else __generate_historical_prices_url(query.symbol)
)
r = make_request(url)
if r.status_code != 200:
raise RuntimeError(r.status_code)
if query.interval == "1d":
data = (
pd.DataFrame(r.json()["data"])[
["date", "open", "high", "low", "close", "volume"]
]
).set_index("date")
# Fill in missing data from current or most recent trading session.
today = pd.to_datetime(datetime.now().date())
if today.weekday() > 4:
day_minus = today.weekday() - 4
today = pd.to_datetime(today - timedelta(days=day_minus))
if today != data.index[-1]:
_today = pd.Series(get_ticker_info(query.symbol))
today_df = pd.Series(dtype="object")
today_df["open"] = round(_today["open"], 2)
today_df["high"] = round(_today["high"], 2)
today_df["low"] = round(_today["low"], 2)
today_df["close"] = round(_today["close"], 2)
if (
query.symbol not in INDEXES
and query.symbol not in TICKER_EXCEPTIONS
):
data = data[data["volume"] > 0]
today_df["volume"] = _today["volume"]
today_df["date"] = today.date()
today_df = pd.DataFrame(today_df).transpose().set_index("date")
data = pd.concat([data, today_df], axis=0)
# If ticker is an index there is no volume data and the types must be set.
if query.symbol in INDEXES or query.symbol in TICKER_EXCEPTIONS:
data = data[["open", "high", "low", "close", "volume"]]
data["open"] = round(data.open.astype(float), 2)
data["high"] = round(data.high.astype(float), 2)
data["low"] = round(data.low.astype(float), 2)
data["close"] = round(data.close.astype(float), 2)
data["volume"] = 0
data.index = pd.to_datetime(data.index)
data = data[data["open"] > 0]
data = data[
(data.index >= pd.to_datetime(query.start_date))
& (data.index <= pd.to_datetime(query.end_date))
]
if query.interval == "1m":
data_list = r.json()["data"]
date: List[datetime] = []
open_: List[float] = []
high: List[float] = []
low: List[float] = []
close: List[float] = []
volume: List[float] = []
calls_volume: List[float] = []
puts_volume: List[float] = []
total_options_volume: List[float] = []
for i in range(0, len(data_list)):
date.append(data_list[i]["datetime"])
open_.append(data_list[i]["price"]["open"])
high.append(data_list[i]["price"]["high"])
low.append(data_list[i]["price"]["low"])
close.append(data_list[i]["price"]["close"])
volume.append(data_list[i]["volume"]["stock_volume"])
calls_volume.append(data_list[i]["volume"]["calls_volume"])
puts_volume.append(data_list[i]["volume"]["puts_volume"])
total_options_volume.append(
data_list[i]["volume"]["total_options_volume"]
)
data = pd.DataFrame()
data["date"] = pd.to_datetime(date)
data["open"] = open_
data["high"] = high
data["low"] = low
data["close"] = close
data["volume"] = volume
data["calls_volume"] = calls_volume
data["puts_volume"] = puts_volume
data["total_options_volume"] = total_options_volume
data = data.set_index("date").sort_index()
data.index = data.index.astype(str)
data = data[data["open"] > 0]
return data.reset_index().to_dict("records")
@staticmethod
def transform_data(
query: CboeMarketIndicesQueryParams, data: List[Dict], **kwargs: Any
) -> List[CboeMarketIndicesData]:
"""Transform the data to the standard format."""
return [CboeMarketIndicesData.model_validate(d) for d in data]

108
openbb_platform/providers/cboe/openbb_cboe/models/options_chains.py
View File

@@ -1,21 +1,23 @@
"""CBOE Options Chains Model."""
"""Cboe Options Chains Model."""
# pylint: disable=invalid-name, unused-argument
from datetime import datetime
from typing import Any, Dict, List, Optional
import pandas as pd
from openbb_cboe.utils.helpers import (
TICKER_EXCEPTIONS,
get_cboe_directory,
get_cboe_index_directory,
get_company_directory,
get_index_directory,
)
from openbb_core.provider.abstract.fetcher import Fetcher
from openbb_core.provider.standard_models.options_chains import (
OptionsChainsData,
OptionsChainsQueryParams,
)
from openbb_core.provider.utils.helpers import make_request
from pydantic import Field, field_validator
from openbb_core.provider.utils.errors import EmptyDataError
from openbb_core.provider.utils.helpers import amake_request
from pandas import DataFrame, DatetimeIndex, Series, to_datetime
from pydantic import Field
class CboeOptionsChainsQueryParams(OptionsChainsQueryParams):
@@ -24,42 +26,22 @@ class CboeOptionsChainsQueryParams(OptionsChainsQueryParams):
Source: https://www.cboe.com/
"""
use_cache: bool = Field(
default=True,
description="When True, the company directories will be cached for"
+ "24 hours and are used to validate symbols."
+ " The results of the function are not cached. Set as False to bypass.",
)
class CboeOptionsChainsData(OptionsChainsData):
"""CBOE Options Chains Data."""
bid_size: int = Field(description="Bid size for the option.")
ask_size: int = Field(description="Ask size for the option.")
theoretical: float = Field(description="Theoretical value of the option.")
open: float = Field(description="Opening price of the option.")
high: float = Field(description="High price of the option.")
low: float = Field(description="Low price of the option.")
last_trade_price: Optional[float] = Field(
description="Last trade price of the option.", default=None
)
tick: Optional[str] = Field(
description="Whether the last tick was up or down in price.", default=None
)
prev_close: float = Field(description="Previous closing price of the option.")
change: float = Field(description="Change in price of the option.")
change_percent: float = Field(description="Change, in percent, of the option.")
implied_volatility: float = Field(description="Implied volatility of the option.")
delta: float = Field(description="Delta of the option.")
gamma: float = Field(description="Gamma of the option.")
vega: float = Field(description="Vega of the option.")
theta: float = Field(description="Theta of the option.")
rho: float = Field(description="Rho of the option.")
last_trade_timestamp: Optional[datetime] = Field(
description="Last trade timestamp of the option.", default=None
)
dte: int = Field(description="Days to expiration for the option.")
@field_validator("expiration", mode="before", check_fields=False)
@classmethod
def date_validate(cls, v): # pylint: disable=E0213
"""Return the datetime object from the date string"""
return datetime.strptime(v, "%Y-%m-%d")
class CboeOptionsChainsFetcher(
Fetcher[
@@ -75,19 +57,20 @@ class CboeOptionsChainsFetcher(
return CboeOptionsChainsQueryParams(**params)
@staticmethod
def extract_data(
async def aextract_data(
query: CboeOptionsChainsQueryParams,
credentials: Optional[Dict[str, str]],
**kwargs: Any,
) -> List[Dict]:
"""Return the raw data from the CBOE endpoint"""
symbol = query.symbol.upper()
"""Return the raw data from the Cboe endpoint"""
INDEXES = get_cboe_index_directory()
SYMBOLS = get_cboe_directory()
symbol = query.symbol.replace("^", "").split(",")[0]
INDEXES = await get_index_directory(use_cache=query.use_cache)
SYMBOLS = await get_company_directory(use_cache=query.use_cache)
INDEXES = INDEXES.set_index("index_symbol")
if symbol not in SYMBOLS.index:
raise RuntimeError(f"{symbol} was not found in the CBOE directory.")
raise RuntimeError(f"{symbol} was not found in the Cboe options directory.")
quotes_url = (
f"https://cdn.cboe.com/api/global/delayed_quotes/options/_{symbol}.json"
@@ -95,22 +78,29 @@ class CboeOptionsChainsFetcher(
else f"https://cdn.cboe.com/api/global/delayed_quotes/options/{symbol}.json"
)
r = make_request(quotes_url)
if r.status_code != 200:
raise RuntimeError(f"No options data found for the symbol, {symbol}.")
return await amake_request(quotes_url)
r_json = r.json()
options_df = pd.DataFrame.from_records(r_json["data"]["options"])
@staticmethod
def transform_data(
query: CboeOptionsChainsQueryParams,
data: List[Dict],
**kwargs: Any,
) -> List[CboeOptionsChainsData]:
"""Transform the data to the standard format"""
if not data:
raise EmptyDataError()
options_df = DataFrame.from_records(data["data"]["options"])
options_df = options_df.rename(
columns={
"option": "contract_symbol",
"iv": "implied_volatility",
"theo": "theoretical",
"last_trade_price": "last_trade_price",
"last_trade_time": "last_trade_timestamp",
"theo": "theoretical_price",
"percent_change": "change_percent",
"prev_day_close": "prev_close",
"last_trade_time": "last_trade_timestamp",
}
)
@@ -126,13 +116,13 @@ class CboeOptionsChainsFetcher(
"C", "call"
).str.replace("P", "put")
option_df_index.strike = [ele.lstrip("0") for ele in option_df_index.strike]
option_df_index.strike = pd.Series(option_df_index.strike).astype(float)
option_df_index.strike = Series(option_df_index.strike).astype(float)
option_df_index.strike = option_df_index.strike * (1 / 1000)
option_df_index.strike = option_df_index.strike.to_list()
option_df_index.expiration = [
ele.lstrip("1") for ele in option_df_index.expiration
]
option_df_index.expiration = pd.DatetimeIndex(
option_df_index.expiration = DatetimeIndex(
option_df_index.expiration, yearfirst=True
).astype(str)
option_df_index = option_df_index.drop(columns=["Ticker"])
@@ -142,12 +132,12 @@ class CboeOptionsChainsFetcher(
quotes = option_df_index.join(options_df)
now = datetime.now()
temp = pd.DatetimeIndex(quotes.expiration)
temp = DatetimeIndex(quotes.expiration)
temp_ = (temp - now).days + 1
quotes["dte"] = temp_
quotes["last_trade_timestamp"] = (
pd.to_datetime(quotes["last_trade_timestamp"], format="%Y-%m-%dT%H:%M:%S")
to_datetime(quotes["last_trade_timestamp"], format="%Y-%m-%dT%H:%M:%S")
.fillna(value="-")
.replace("-", None)
)
@@ -159,15 +149,9 @@ class CboeOptionsChainsFetcher(
quotes["bid_size"] = quotes["bid_size"].astype("int64")
quotes["ask_size"] = quotes["ask_size"].astype("int64")
quotes["prev_close"] = round(quotes["prev_close"], 2)
quotes["change_percent"] = round(quotes["change_percent"], 2)
quotes["change_percent"] = round(quotes["change_percent"] / 100, 4)
return quotes.reset_index().to_dict("records")
@staticmethod
def transform_data(
query: CboeOptionsChainsQueryParams,
data: dict,
**kwargs: Any,
) -> List[CboeOptionsChainsData]:
"""Transform the data to the standard format"""
return [CboeOptionsChainsData.model_validate(d) for d in data]
return [
CboeOptionsChainsData.model_validate(d)
for d in quotes.reset_index().to_dict("records")
]

452
openbb_platform/providers/cboe/openbb_cboe/utils/helpers.py
View File

@@ -1,92 +1,128 @@
"""CBOE Helpers Module."""
"""Cboe Helpers"""
# pylint: disable=expression-not-assigned, unused-argument
from datetime import date, timedelta
from datetime import date as dateType
from io import BytesIO, StringIO
from typing import Any, Dict, List, Optional
from typing import Any, List, Literal, Optional
import pandas as pd
import requests
import requests_cache
from aiohttp_client_cache import SQLiteBackend
from aiohttp_client_cache.session import CachedSession
from openbb_core.app.utils import get_user_cache_directory
from openbb_core.provider.utils.helpers import to_snake_case
cache_dir = get_user_cache_directory()
cboe_session = requests_cache.CachedSession(
f"{cache_dir}/http/cboe_directories", expire_after=timedelta(days=7)
)
from openbb_core.provider.utils.client import ClientResponse
from openbb_core.provider.utils.helpers import amake_request, to_snake_case
from pandas import DataFrame, read_csv
TICKER_EXCEPTIONS = ["NDX", "RUT"]
US_INDEX_COLUMNS = {
"symbol": "symbol",
"name": "name",
"current_price": "price",
"open": "open",
"high": "high",
"low": "low",
"close": "close",
"prev_day_close": "prev_close",
"price_change": "change",
"price_change_percent": "change_percent",
"last_trade_time": "last_trade_timestamp",
}
CONSTITUENTS_EU = Literal[ # pylint: disable=invalid-name
"BAT20P",
"BBE20P",
"BCH20P",
"BCHM30P",
"BDE40P",
"BDEM50P",
"BDES50P",
"BDK25P",
"BEP50P",
"BEPACP",
"BEPBUS",
"BEPCNC",
"BEPCONC",
"BEPCONS",
"BEPENGY",
"BEPFIN",
"BEPHLTH",
"BEPIND",
"BEPNEM",
"BEPTEC",
"BEPTEL",
"BEPUTL",
"BEPXUKP",
"BES35P",
"BEZ50P",
"BEZACP",
"BFI25P",
"BFR40P",
"BFRM20P",
"BIE20P",
"BIT40P",
"BNL25P",
"BNLM25P",
"BNO25G",
"BNORD40P",
"BPT20P",
"BSE30P",
"BUK100P",
"BUK250P",
"BUK350P",
"BUKAC",
"BUKBISP",
"BUKBUS",
"BUKCNC",
"BUKCONC",
"BUKCONS",
"BUKENGY",
"BUKFIN",
"BUKHI50P",
"BUKHLTH",
"BUKIND",
"BUKLO50P",
"BUKMINP",
"BUKNEM",
"BUKSC",
"BUKTEC",
"BUKTEL",
"BUKUTL",
]
EUR_INDEX_COLUMNS = {
"name": "name",
"isin": "isin",
"currency": "currency",
"current_price": "price",
"open": "open",
"high": "high",
"low": "low",
"close": "close",
"prev_day_close": "prev_close",
"price_change": "change",
"price_change_percent": "change_percent",
"last_trade_time": "last_trade_timestamp",
}
EUR_INDEX_CONSTITUENTS_COLUMNS = {
"symbol": "symbol",
"current_price": "price",
"open": "open",
"high": "high",
"low": "low",
"close": "close",
"volume": "volume",
"seqno": "seqno",
"prev_day_close": "prev_close",
"price_change": "change",
"price_change_percent": "change_percent",
"last_trade_time": "last_trade_timestamp",
"exchange_id": "exchange_id",
"tick": "tick",
"security_type": "type",
}
cache_dir = get_user_cache_directory()
backend = SQLiteBackend(f"{cache_dir}/http/cboe_directories", expire_after=3600 * 24)
def get_cboe_directory(**kwargs) -> pd.DataFrame:
"""Get the US Listings Directory for the CBOE.
async def response_callback(response: ClientResponse, _: Any):
"""Callback for HTTP Client Response."""
content_type = response.headers.get("Content-Type", "")
if "application/json" in content_type:
return await response.json()
if "text" in content_type:
return await response.text()
return await response.read()
async def get_cboe_data(url, use_cache: bool = True, **kwargs) -> Any:
"""Generic Cboe HTTP request."""
if use_cache is True:
async with CachedSession(cache=backend) as cached_session:
try:
response = await cached_session.get(url, timeout=10, **kwargs)
data = await response_callback(response, None)
finally:
await cached_session.close()
else:
data = await amake_request(url, response_callback=response_callback)
return data
async def get_company_directory(use_cache: bool = True, **kwargs) -> DataFrame:
"""
Get the US Company Directory for Cboe options. If use_cache is True,
the data will be cached for 24 hours.
Returns
-------
pd.DataFrame: CBOE_DIRECTORY
DataFrame of the CBOE listings directory
DataFrame: Pandas DataFrame of the Cboe listings directory
"""
r = cboe_session.get(
"https://www.cboe.com/us/options/symboldir/equity_index_options/?download=csv",
timeout=10,
)
url = "https://www.cboe.com/us/options/symboldir/equity_index_options/?download=csv"
if r.status_code != 200:
raise RuntimeError(r.status_code)
results = await get_cboe_data(url, use_cache)
r_json = StringIO(r.text)
response = BytesIO(results)
CBOE_DIRECTORY = pd.read_csv(r_json)
directory = read_csv(response)
CBOE_DIRECTORY = CBOE_DIRECTORY.rename(
directory = directory.rename(
columns={
" Stock Symbol": "symbol",
" DPM Name": "dpm_name",
@@ -95,149 +131,33 @@ def get_cboe_directory(**kwargs) -> pd.DataFrame:
}
).set_index("symbol")
return CBOE_DIRECTORY.astype(str)
return directory.astype(str)
def get_cboe_index_directory(**kwargs) -> pd.DataFrame:
"""Get the US Listings Directory for the CBOE
async def get_index_directory(use_cache: bool = True, **kwargs) -> DataFrame:
"""
Get the Cboe Index Directory. If use_cache is True,
the data will be cached for 24 hours.
Returns
-------
pd.DataFrame: CBOE_INDEXES
--------
List[Dict]: A list of dictionaries containing the index information.
"""
r = cboe_session.get(
"https://cdn.cboe.com/api/global/us_indices/definitions/all_indices.json",
timeout=10,
)
url = "https://cdn.cboe.com/api/global/us_indices/definitions/all_indices.json"
if r.status_code != 200:
raise requests.HTTPError(r.status_code)
results = await get_cboe_data(url, use_cache=use_cache)
CBOE_INDEXES = pd.DataFrame(r.json())
[result.pop("featured") for result in results]
[result.pop("featured_order") for result in results]
[result.pop("display") for result in results]
results = DataFrame(results)
results = results[results["source"] != "morningstar"]
CBOE_INDEXES = CBOE_INDEXES.rename(
columns={
"calc_end_time": "close_time",
"calc_start_time": "open_time",
"index_symbol": "symbol",
"mkt_data_delay": "data_delay",
},
)
indices_order: List[str] = [
"symbol",
"name",
"description",
"currency",
"open_time",
"close_time",
"tick_days",
"tick_frequency",
"tick_period",
"time_zone",
"data_delay",
]
CBOE_INDEXES = pd.DataFrame(CBOE_INDEXES, columns=indices_order).set_index("symbol")
idx = (
(CBOE_INDEXES.time_zone.str.contains("America/Chicago"))
& (CBOE_INDEXES.currency.str.contains("USD"))
& (CBOE_INDEXES.description.str.contains("Daily Risk Control") == 0)
& (CBOE_INDEXES.name.str.contains("OEX%-SML% INDEX") == 0)
& (CBOE_INDEXES.name.str.contains("Defined Risk Volatility Income") == 0)
& (CBOE_INDEXES.description.str.contains("is designed to track") == 0)
)
return CBOE_INDEXES[idx]
return results
def get_ticker_info(symbol: str, **kwargs) -> Dict[str, Any]:
symbol = symbol.upper()
SYMBOLS = get_cboe_directory()
INDEXES = get_cboe_index_directory()
data: Dict[str, Any] = {}
if symbol not in SYMBOLS.index and symbol not in INDEXES.index:
raise RuntimeError(f"Data not found for: {symbol}")
url = (
f"https://cdn.cboe.com/api/global/delayed_quotes/quotes/_{symbol}.json"
if symbol in INDEXES.index or symbol in TICKER_EXCEPTIONS
else f"https://cdn.cboe.com/api/global/delayed_quotes/quotes/{symbol}.json"
)
r = requests.get(url, timeout=10)
if r.status_code not in set([200, 403]):
raise requests.HTTPError(r.status_code)
if r.status_code == 403:
raise RuntimeError(f"Data was not found for, {symbol}.")
data = r.json()["data"]
if symbol in SYMBOLS.index.to_list():
data.update({"name": SYMBOLS.at[symbol, "name"]})
if symbol in INDEXES.index.to_list():
data.update({"name": INDEXES.at[symbol, "name"]})
_data = pd.DataFrame.from_dict(data, orient="index").transpose()
_data = _data.rename(
columns={
"current_price": "price",
"prev_day_close": "prev_close",
"price_change": "change",
"price_change_percent": "change_percent",
"last_trade_time": "last_trade_timestamp",
"security_type": "type",
}
)
return _data.transpose()[0].to_dict()
def get_ticker_iv(symbol: str, **kwargs) -> Dict[str, float]:
"""Get annualized high/low historical and implied volatility over 30/60/90 day windows.
Parameters
----------
symbol: str
The loaded ticker
Returns
-------
pd.DataFrame: ticker_iv
"""
symbol = symbol.upper()
INDEXES = get_cboe_index_directory().index.to_list()
quotes_iv_url = (
"https://cdn.cboe.com/api/global/delayed_quotes/historical_data/_"
f"{symbol}"
".json"
if symbol in TICKER_EXCEPTIONS or symbol in INDEXES
else f"https://cdn.cboe.com/api/global/delayed_quotes/historical_data/{symbol}.json"
)
h_iv = requests.get(quotes_iv_url, timeout=10)
if h_iv.status_code not in set([200, 403]):
raise requests.HTTPError(h_iv.status_code)
if h_iv.status_code == 403:
raise RuntimeError(f"Data was not found for, {symbol}.")
data = pd.DataFrame(h_iv.json())[2:-1]["data"].rename(f"{symbol}")
return data.to_dict()
def list_futures(**kwargs) -> List[dict]:
async def list_futures(**kwargs) -> List[dict]:
"""List of CBOE futures and their underlying symbols.
Returns
@@ -246,24 +166,22 @@ def list_futures(**kwargs) -> List[dict]:
Pandas DataFrame with results.
"""
r = requests.get(
"https://cdn.cboe.com/api/global/delayed_quotes/symbol_book/futures-roots.json",
timeout=10,
r = await get_cboe_data(
"https://cdn.cboe.com/api/global/delayed_quotes/symbol_book/futures-roots.json"
)
data = r.get("data")
[d.pop("sort_order") for d in data]
if r.status_code != 200:
raise requests.HTTPError(r.status_code)
return r.json()["data"]
return data
def get_settlement_prices(
settlement_date: Optional[date] = None,
async def get_settlement_prices(
settlement_date: Optional[dateType] = None,
options: bool = False,
archives: bool = False,
final_settlement: bool = False,
**kwargs,
) -> pd.DataFrame:
) -> DataFrame:
"""Gets the settlement prices of CBOE futures.
Parameters
@@ -279,18 +197,20 @@ def get_settlement_prices(
Returns
-------
pd.DataFrame
DataFrame
Pandas DataFrame with results.
"""
url = ""
if archives is True:
url = "https://cdn.cboe.com/resources/futures/archive/volume-and-price/CFE_FinalSettlement_Archive.csv"
if settlement_date is not None:
url = f"https://www.cboe.com/us/futures/market_statistics/settlement/csv?dt={settlement_date}"
url = (
"https://www.cboe.com/us/futures/market_statistics"
+ f"/settlement/csv?dt={settlement_date}"
)
if options is True:
url = f"https://www.cboe.com/us/futures/market_statistics/settlement/csv?options=t&dt={settlement_date}"
url = (
"https://www.cboe.com/us/futures/market_statistics/"
+ f"settlement/csv?options=t&dt={settlement_date}"
)
if settlement_date is None:
url = "https://www.cboe.com/us/futures/market_statistics/settlement/csv"
if options is True:
@@ -299,20 +219,18 @@ def get_settlement_prices(
if final_settlement is True:
url = "https://www.cboe.com/us/futures/market_statistics/final_settlement_prices/csv/"
r = requests.get(url, timeout=10)
if archives is True:
url = (
"https://cdn.cboe.com/resources/futures/archive"
+ "/volume-and-price/CFE_FinalSettlement_Archive.csv"
)
if r.status_code != 200:
raise RuntimeError(r.status_code)
response = await get_cboe_data(url, use_cache=False, **kwargs)
data = pd.read_csv(BytesIO(r.content), index_col=None, parse_dates=True)
data = read_csv(StringIO(response), index_col=None, parse_dates=True)
if data.empty:
error_string = (
f"No results found for, {settlement_date}."
if settlement_date is not None
else "No results found."
)
raise RuntimeError(error_string)
return DataFrame()
data.columns = [to_snake_case(c) for c in data.columns]
data = data.rename(columns={"expiration_date": "expiration"})
@@ -320,78 +238,4 @@ def get_settlement_prices(
if len(data) > 0:
return data
return pd.DataFrame()
class Europe:
"""Class for European CBOE data."""
@staticmethod
def get_all_index_definitions(**kwargs) -> Dict[Any, Any]:
"""Get the full list of European index definitions.
Returns
-------
Dict[Any, Any]
Dictionary with results.
"""
r = cboe_session.get(
"https://cdn.cboe.com/api/global/european_indices/definitions/all-definitions.json",
timeout=10,
)
if r.status_code != 200:
raise requests.HTTPError(r.status_code)
return r.json()["data"]
@staticmethod
def list_indices(**kwargs) -> List[Dict]:
"""Gets names, currencies, ISINs, regions, and symbols for European indices.
Returns
-------
Dict[str, str]
List of dictionaries with the results.
"""
data = Europe.get_all_index_definitions()
data = (
pd.DataFrame.from_records(pd.DataFrame(data)["index"])
.drop(columns=["short_name"])
.rename(columns={"long_name": "name"})
)
return data.to_dict("records")
@staticmethod
def list_index_constituents(symbol: str, **kwargs) -> List[str]:
"""List symbols for constituents of a European index.
Parameters
----------
symbol: str
The symbol of the index.
Returns
-------
List[str]
List of constituents as ticker symbols.
"""
SYMBOLS = pd.DataFrame(Europe.list_indices())["symbol"].to_list()
symbol = symbol.upper()
if symbol not in SYMBOLS:
raise RuntimeError(
f"The symbol, {symbol}, was not found in the CBOE European Index directory.",
)
url = f"https://cdn.cboe.com/api/global/european_indices/definitions/{symbol}.json"
r = requests.get(url, timeout=10)
if r.status_code != 200:
raise requests.HTTPError(r.status_code)
r_json = r.json()["constituents"]
return [r_json[i]["constituent_symbol"] for i in range(0, len(r_json))]
return DataFrame()

1052
openbb_platform/providers/cboe/poetry.lock generated vendored
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3
openbb_platform/providers/cboe/pyproject.toml vendored
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@@ -8,7 +8,8 @@ packages = [{ include = "openbb_cboe" }]
[tool.poetry.dependencies]
python = "^3.8"
requests-cache = "^1.1.0"
aiohttp-client-cache = "^0.10.0"
aiosqlite = "^0.19.0"
openbb-core = "^1.1.1"
[build-system]

1174
openbb_platform/providers/cboe/tests/record/http/test_cboe_fetchers/test_cboe_available_indices_fetcher.yaml vendored
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6018
openbb_platform/providers/cboe/tests/record/http/test_cboe_fetchers/test_cboe_equity_historical_fetcher.yaml vendored
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114
openbb_platform/providers/cboe/tests/record/http/test_cboe_fetchers/test_cboe_equity_info_fetcher.yaml vendored
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@@ -1,114 +0,0 @@
interactions:
- request:
body: null
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
method: GET
uri: https://cdn.cboe.com/api/global/delayed_quotes/quotes/AAPL.json
response:
body:
string: !!binary |
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headers:
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Content-Encoding:
- gzip
Content-Type:
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Date:
- Tue, 26 Sep 2023 19:06:36 GMT
ETag:
- W/"23e87da6795e2433a5ea9cc52e3c77b6"
Last-Modified:
- Tue, 26 Sep 2023 19:05:45 GMT
Server:
- cloudflare
Transfer-Encoding:
- chunked
Via:
- 1.1 5888333a47f4bcb4270f45fea45f08bc.cloudfront.net (CloudFront)
X-Amz-Cf-Id:
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x-amz-server-side-encryption:
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status:
code: 200
message: OK
- request:
body: null
headers:
Accept:
- '*/*'
Accept-Encoding:
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Connection:
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method: GET
uri: https://cdn.cboe.com/api/global/delayed_quotes/historical_data/AAPL.json
response:
body:
string: !!binary |
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headers:
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Content-Encoding:
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Content-Type:
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Date:
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ETag:
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Via:
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X-Amz-Cf-Id:
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X-Amz-Cf-Pop:
- MIA3-P4
X-Cache:
- RefreshHit from cloudfront
x-amz-server-side-encryption:
- AES256
status:
code: 200
message: OK
version: 1

2255
openbb_platform/providers/cboe/tests/record/http/test_cboe_fetchers/test_cboe_equity_quote_fetcher.yaml vendored Normal file
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3027
openbb_platform/providers/cboe/tests/record/http/test_cboe_fetchers/test_cboe_equity_search_fetcher.yaml vendored
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424
openbb_platform/providers/cboe/tests/record/http/test_cboe_fetchers/test_cboe_european_index_constituents_fetcher.yaml vendored
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@@ -1,424 +0,0 @@
interactions:
- request:
body: null
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
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method: GET
uri: https://cdn.cboe.com/api/global/european_indices/definitions/all-definitions.json
response:
body:
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version: 1

504
openbb_platform/providers/cboe/tests/record/http/test_cboe_fetchers/test_cboe_european_indices_fetcher.yaml vendored
View File

@@ -1,504 +0,0 @@
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148
openbb_platform/providers/cboe/tests/record/http/test_cboe_fetchers/test_cboe_futures_curve_fetcher.yaml vendored
View File

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177
openbb_platform/providers/cboe/tests/record/http/test_cboe_fetchers/test_cboe_index_constituents_fetcher.yaml vendored Normal file
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Connection:
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Content-Encoding:
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Content-Type:
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Date:
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Etag:
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Last-Modified:
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Server:
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Transfer-Encoding:
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Via:
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X-Amz-Cf-Id:
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X-Amz-Cf-Pop:
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X-Cache:
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x-amz-server-side-encryption:
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status:
code: 200
message: OK
version: 1

1231
openbb_platform/providers/cboe/tests/record/http/test_cboe_fetchers/test_cboe_index_historical_fetcher.yaml vendored
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File diff suppressed because it is too large Load Diff

1178
openbb_platform/providers/cboe/tests/record/http/test_cboe_fetchers/test_cboe_index_search_fetcher.yaml vendored
View File

File diff suppressed because it is too large Load Diff

710
openbb_platform/providers/cboe/tests/record/http/test_cboe_fetchers/test_cboe_index_snapshots_fetcher.yaml vendored
View File

@@ -3,650 +3,84 @@ interactions:
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headers:
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- Mon, 18 Dec 2023 15:29:37 GMT
Server:
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x-amz-server-side-encryption:

346
openbb_platform/providers/cboe/tests/record/http/test_cboe_fetchers/test_cboe_market_indices_fetcher.yaml vendored
View File

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8236
openbb_platform/providers/cboe/tests/record/http/test_cboe_fetchers/test_cboe_options_chains_fetcher.yaml vendored
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148
openbb_platform/providers/cboe/tests/test_cboe_fetchers.py
View File

@@ -1,7 +1,10 @@
"""CBOE Fetchers Tests.
The CBOE provider extension uses request caching.
So, when an item like a symbol directory is already cached, the cassette recorder does
For tests, set all functions using cache with the `use_cache` parameter to `False`.
When an item like a symbol directory is already cached, the cassette recorder does
not record the request event. If functions share a cached resource, it will only capture
the cassette for the first instance.
@@ -13,23 +16,13 @@ from datetime import date
import pytest
from openbb_cboe.models.available_indices import CboeAvailableIndicesFetcher
from openbb_cboe.models.equity_historical import CboeEquityHistoricalFetcher
from openbb_cboe.models.equity_info import CboeEquityInfoFetcher
from openbb_cboe.models.equity_quote import CboeEquityQuoteFetcher
from openbb_cboe.models.equity_search import CboeEquitySearchFetcher
from openbb_cboe.models.european_index_constituents import (
CboeEuropeanIndexConstituentsFetcher,
)
from openbb_cboe.models.european_indices import (
CboeEuropeanIndicesFetcher,
)
from openbb_cboe.models.futures_curve import CboeFuturesCurveFetcher
from openbb_cboe.models.index_historical import (
CboeIndexHistoricalFetcher,
)
from openbb_cboe.models.index_constituents import CboeIndexConstituentsFetcher
from openbb_cboe.models.index_historical import CboeIndexHistoricalFetcher
from openbb_cboe.models.index_search import CboeIndexSearchFetcher
from openbb_cboe.models.index_snapshots import CboeIndexSnapshotsFetcher
from openbb_cboe.models.market_indices import (
CboeMarketIndicesFetcher,
)
from openbb_cboe.models.options_chains import CboeOptionsChainsFetcher
from openbb_core.app.service.user_service import UserService
@@ -38,33 +31,6 @@ test_credentials = UserService().default_user_settings.credentials.model_dump(
)
@pytest.mark.record_http
def test_cboe_available_indices_fetcher(credentials=test_credentials):
params = {}
fetcher = CboeAvailableIndicesFetcher()
result = fetcher.test(params, credentials)
assert result is None
@pytest.mark.record_http
def test_cboe_index_search_fetcher(credentials=test_credentials):
params = {}
fetcher = CboeIndexSearchFetcher()
result = fetcher.test(params, credentials)
assert result is None
@pytest.mark.record_http
def test_cboe_options_chains_fetcher(credentials=test_credentials):
params = {"symbol": "AAPL"}
fetcher = CboeOptionsChainsFetcher()
result = fetcher.test(params, credentials)
assert result is None
@pytest.fixture(scope="module")
def vcr_config():
return {
@@ -76,10 +42,28 @@ def vcr_config():
@pytest.mark.record_http
def test_cboe_equity_search_fetcher(credentials=test_credentials):
params = {}
def test_cboe_index_historical_fetcher(credentials=test_credentials):
params = {"symbol": "AAVE10RP", "use_cache": False}
fetcher = CboeEquitySearchFetcher()
fetcher = CboeIndexHistoricalFetcher()
result = fetcher.test(params, credentials)
assert result is None
@pytest.mark.record_http
def test_cboe_index_constituents_fetcher(credentials=test_credentials):
params = {"symbol": "BUKBUS"}
fetcher = CboeIndexConstituentsFetcher()
result = fetcher.test(params, credentials)
assert result is None
@pytest.mark.record_http
def test_cboe_index_search_fetcher(credentials=test_credentials):
params = {"query": "uk", "use_cache": False}
fetcher = CboeIndexSearchFetcher()
result = fetcher.test(params, credentials)
assert result is None
@@ -91,6 +75,7 @@ def test_cboe_equity_historical_fetcher(credentials=test_credentials):
"start_date": date(2023, 1, 1),
"end_date": date(2023, 1, 10),
"interval": "1d",
"use_cache": False,
}
fetcher = CboeEquityHistoricalFetcher()
@@ -99,10 +84,37 @@ def test_cboe_equity_historical_fetcher(credentials=test_credentials):
@pytest.mark.record_http
def test_cboe_equity_info_fetcher(credentials=test_credentials):
params = {"symbol": "AAPL"}
def test_cboe_available_indices_fetcher(credentials=test_credentials):
params = {"use_cache": False}
fetcher = CboeEquityInfoFetcher()
fetcher = CboeAvailableIndicesFetcher()
result = fetcher.test(params, credentials)
assert result is None
@pytest.mark.record_http
def test_cboe_options_chains_fetcher(credentials=test_credentials):
params = {"symbol": "AAPL", "use_cache": False}
fetcher = CboeOptionsChainsFetcher()
result = fetcher.test(params, credentials)
assert result is None
@pytest.mark.record_http
def test_cboe_equity_search_fetcher(credentials=test_credentials):
params = {"query": "ETF", "use_cache": False}
fetcher = CboeEquitySearchFetcher()
result = fetcher.test(params, credentials)
assert result is None
@pytest.mark.record_http
def test_cboe_equity_quote_fetcher(credentials=test_credentials):
params = {"symbol": "AAPL", "use_cache": False}
fetcher = CboeEquityQuoteFetcher()
result = fetcher.test(params, credentials)
assert result is None
@@ -116,49 +128,9 @@ def test_cboe_futures_curve_fetcher(credentials=test_credentials):
assert result is None
@pytest.mark.record_http
def test_cboe_european_index_constituents_fetcher(credentials=test_credentials):
params = {"symbol": "BUKBUS"}
fetcher = CboeEuropeanIndexConstituentsFetcher()
result = fetcher.test(params, credentials)
assert result is None
@pytest.mark.record_http
def test_cboe_european_indices_fetcher(credentials=test_credentials):
params = {
"symbol": "BUKBUS",
"start_date": date(2023, 1, 1),
"end_date": date(2023, 1, 10),
}
fetcher = CboeEuropeanIndicesFetcher()
result = fetcher.test(params, credentials)
assert result is None
@pytest.mark.record_http
def test_cboe_market_indices_fetcher(credentials=test_credentials):
params = {"symbol": "AAVE10RP"}
fetcher = CboeMarketIndicesFetcher()
result = fetcher.test(params, credentials)
assert result is None
@pytest.mark.record_http
def test_cboe_index_historical_fetcher(credentials=test_credentials):
params = {"symbol": "AAVE10RP"}
fetcher = CboeIndexHistoricalFetcher()
result = fetcher.test(params, credentials)
assert result is None
@pytest.mark.record_http
def test_cboe_index_snapshots_fetcher(credentials=test_credentials):
params = {}
params = {"region": "eu"}
fetcher = CboeIndexSnapshotsFetcher()
result = fetcher.test(params, credentials)

42
openbb_platform/providers/fmp/openbb_fmp/models/index_constituents.py
View File

@@ -1,15 +1,19 @@
"""FMP Index Constituents Model."""
from datetime import datetime
from typing import Any, Dict, List, Optional
from datetime import (
date as dateType,
datetime,
)
from typing import Any, Dict, List, Literal, Optional, Union
from openbb_core.provider.abstract.fetcher import Fetcher
from openbb_core.provider.standard_models.index_constituents import (
IndexConstituentsData,
IndexConstituentsQueryParams,
)
from openbb_core.provider.utils.descriptions import DATA_DESCRIPTIONS
from openbb_fmp.utils.helpers import get_data_many
from pydantic import field_validator
from pydantic import Field, field_validator
class FMPIndexConstituentsQueryParams(IndexConstituentsQueryParams):
@@ -20,11 +24,41 @@ class FMPIndexConstituentsQueryParams(IndexConstituentsQueryParams):
https://site.financialmodelingprep.com/developer/docs/list-of-nasdaq-companies-api/
"""
index: Literal["dowjones", "sp500", "nasdaq"] = Field(
default="dowjones",
)
class FMPIndexConstituentsData(IndexConstituentsData):
"""FMP Index Constituents Data."""
__alias_dict__ = {"headquarter": "headQuarter"}
__alias_dict__ = {
"headquarter": "headQuarter",
"date_first_added": "dateFirstAdded",
"sub_sector": "subSector",
}
sector: str = Field(
description="Sector the constituent company in the index belongs to."
)
sub_sector: Optional[str] = Field(
default=None,
description="Sub-sector the constituent company in the index belongs to.",
)
headquarter: Optional[str] = Field(
default=None,
description="Location of the headquarter of the constituent company in the index.",
)
date_first_added: Optional[Union[dateType, str]] = Field(
default=None, description="Date the constituent company was added to the index."
)
cik: Optional[int] = Field(
description=DATA_DESCRIPTIONS.get("cik", ""), default=None
)
founded: Optional[Union[dateType, str]] = Field(
default=None,
description="Founding year of the constituent company in the index.",
)
@field_validator("dateFirstAdded", mode="before", check_fields=False)
@classmethod

52
openbb_platform/providers/intrinio/openbb_intrinio/models/options_chains.py
View File

@@ -28,7 +28,7 @@ class IntrinioOptionsChainsQueryParams(OptionsChainsQueryParams):
"""
date: Optional[dateType] = Field(
description="Date for which the options chains are returned."
default=None, description="The end-of-day date for options chains data."
)
@@ -42,7 +42,19 @@ class IntrinioOptionsChainsData(OptionsChainsData):
"option_type": "type",
}
@field_validator("expiration", "date", mode="before", check_fields=False)
exercise_style: Optional[str] = Field(
default=None,
description="The exercise style of the option, American or European.",
)
@field_validator(
"date",
"close_time",
"close_ask_time",
"close_bid_time",
mode="before",
check_fields=False,
)
@classmethod
def date_validate(cls, v): # pylint: disable=E0213
"""Return the datetime object from the date string."""
@@ -60,15 +72,12 @@ class IntrinioOptionsChainsFetcher(
@staticmethod
def transform_query(params: Dict[str, Any]) -> IntrinioOptionsChainsQueryParams:
"""Transform the query."""
transform_params = params
now = datetime.now().date()
if params.get("date") is None:
transform_params["date"] = (now - timedelta(days=1)).strftime("%Y-%m-%d")
elif isinstance(params["date"], dateType):
transform_params["date"] = params["date"].strftime("%Y-%m-%d")
else:
transform_params["date"] = parser.parse(params["date"]).date()
transform_params = params.copy()
if params.get("date") is not None:
if isinstance(params["date"], dateType):
transform_params["date"] = params["date"].strftime("%Y-%m-%d")
else:
transform_params["date"] = parser.parse(params["date"]).date()
return IntrinioOptionsChainsQueryParams(**transform_params)
@@ -89,18 +98,24 @@ class IntrinioOptionsChainsFetcher(
f"{base_url}/expirations/{query.symbol}/eod?"
f"after={date}&api_key={api_key}"
)
expiration = await get_data_many(url, "expirations", **kwargs)
return [
f"{base_url}/chain/{query.symbol}/{expiration}/eod?date={query.date}&api_key={api_key}"
for expiration in expiration
]
expirations = await get_data_many(url, "expirations", **kwargs)
def generate_url(expiration) -> str:
url = f"{base_url}/chain/{query.symbol}/{expiration}/eod?date="
if query.date is not None:
url += date
return url + f"&api_key={api_key}"
return [generate_url(expiration) for expiration in expirations]
async def callback(response: ClientResponse, _: Any) -> list:
"""Return the response."""
response_data = await response.json()
return response_data.get("chain", [])
date = get_weekday(query.date)
date = datetime.now().date() if query.date is None else query.date
date = get_weekday(date)
results = await amake_requests(await get_urls(date), callback, **kwargs)
if not results:
@@ -115,4 +130,7 @@ class IntrinioOptionsChainsFetcher(
) -> List[IntrinioOptionsChainsData]:
"""Return the transformed data."""
data = [{**item["option"], **item["prices"]} for item in data]
data = sorted(
data, key=lambda x: (x["expiration"], x["strike"], x["type"]), reverse=False
)
return [IntrinioOptionsChainsData.model_validate(d) for d in data]

7433
openbb_platform/providers/intrinio/tests/record/http/test_intrinio_fetchers/test_intrinio_options_chains_fetcher.yaml vendored
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2
openbb_platform/providers/intrinio/tests/test_intrinio_fetchers.py
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@@ -115,7 +115,7 @@ def test_intrinio_equity_quote_fetcher(credentials=test_credentials):
@pytest.mark.record_http
def test_intrinio_options_chains_fetcher(credentials=test_credentials):
params = {"symbol": "AAPL", "date": "2023-09-15"}
params = {"symbol": "AAPL", "date": date(2023, 9, 15)}
fetcher = IntrinioOptionsChainsFetcher()
result = fetcher.test(params, credentials)

80
website/content/platform/data_models/EuropeanIndexConstituents.md vendored
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@@ -1,80 +0,0 @@
---
title: European Index Constituents
description: OpenBB Platform Data Model
---
<!-- markdownlint-disable MD012 MD031 MD033 -->
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
---
## Implementation details
### Class names
| Model name | Parameters class | Data class |
| ---------- | ---------------- | ---------- |
| `EuropeanIndexConstituents` | `EuropeanIndexConstituentsQueryParams` | `EuropeanIndexConstituentsData` |
### Import Statement
```python
from openbb_core.provider.standard_models.european_index_constituents import (
EuropeanIndexConstituentsData,
EuropeanIndexConstituentsQueryParams,
)
```
## Parameters
<Tabs>
<TabItem value="standard" label="Standard">
| Name | Type | Description | Default | Optional |
| ---- | ---- | ----------- | ------- | -------- |
| symbol | Union[str, List[str]] | Symbol to get data for. | | False |
| provider | Literal['cboe'] | The provider to use for the query, by default None. If None, the provider specified in defaults is selected or 'cboe' if there is no default. | cboe | True |
</TabItem>
</Tabs>
## Data
<Tabs>
<TabItem value="standard" label="Standard">
| Name | Type | Description |
| ---- | ---- | ----------- |
| symbol | str | Symbol representing the entity requested in the data. The symbol is the constituent company in the index. |
| price | float | Current price of the constituent company in the index. |
| open | float | The open price. |
| high | float | The high price. |
| low | float | The low price. |
| close | float | The close price. |
| volume | float | The trading volume. |
</TabItem>
<TabItem value='cboe' label='cboe'>
| Name | Type | Description |
| ---- | ---- | ----------- |
| symbol | str | Symbol representing the entity requested in the data. The symbol is the constituent company in the index. |
| price | float | Current price of the constituent company in the index. |
| open | float | The open price. |
| high | float | The high price. |
| low | float | The low price. |
| close | float | The close price. |
| volume | float | The trading volume. |
| prev_close | float | Previous closing price. |
| change | float | Change in price. |
| change_percent | float | Change in price as a percentage. |
| tick | str | Whether the last sale was an up or down tick. |
| last_trade_timestamp | datetime | Last trade timestamp for the symbol. |
| exchange_id | int | The Exchange ID number. |
| seqno | int | Sequence number of the last trade on the tape. |
| asset_type | str | Type of asset. |
</TabItem>
</Tabs>

79
website/content/platform/data_models/EuropeanIndices.md vendored
View File

@@ -1,79 +0,0 @@
---
title: Historical European Indices
description: OpenBB Platform Data Model
---
<!-- markdownlint-disable MD012 MD031 MD033 -->
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
---
## Implementation details
### Class names
| Model name | Parameters class | Data class |
| ---------- | ---------------- | ---------- |
| `EuropeanIndices` | `EuropeanIndicesQueryParams` | `EuropeanIndicesData` |
### Import Statement
```python
from openbb_core.provider.standard_models.european_indices import (
EuropeanIndicesData,
EuropeanIndicesQueryParams,
)
```
## Parameters
<Tabs>
<TabItem value="standard" label="Standard">
| Name | Type | Description | Default | Optional |
| ---- | ---- | ----------- | ------- | -------- |
| symbol | Union[str, List[str]] | Symbol to get data for. | | False |
| start_date | Union[date, str] | Start date of the data, in YYYY-MM-DD format. | None | True |
| end_date | Union[date, str] | End date of the data, in YYYY-MM-DD format. | None | True |
| provider | Literal['cboe'] | The provider to use for the query, by default None. If None, the provider specified in defaults is selected or 'cboe' if there is no default. | cboe | True |
</TabItem>
<TabItem value='cboe' label='cboe'>
| Name | Type | Description | Default | Optional |
| ---- | ---- | ----------- | ------- | -------- |
| symbol | Union[str, List[str]] | Symbol to get data for. | | False |
| start_date | Union[date, str] | Start date of the data, in YYYY-MM-DD format. | None | True |
| end_date | Union[date, str] | End date of the data, in YYYY-MM-DD format. | None | True |
| provider | Literal['cboe'] | The provider to use for the query, by default None. If None, the provider specified in defaults is selected or 'cboe' if there is no default. | cboe | True |
| interval | Literal['1m', '1d'] | Data granularity. | 1d | True |
</TabItem>
</Tabs>
## Data
<Tabs>
<TabItem value="standard" label="Standard">
| Name | Type | Description |
| ---- | ---- | ----------- |
| date | datetime | The date of the data. |
| close | float | The close price. |
</TabItem>
<TabItem value='cboe' label='cboe'>
| Name | Type | Description |
| ---- | ---- | ----------- |
| date | datetime | The date of the data. |
| close | float | The close price. |
| open | float | Opening price for the interval. Only valid when interval is 1m. |
| high | float | High price for the interval. Only valid when interval is 1m. |
| low | float | Low price for the interval. Only valid when interval is 1m. |
| utc_datetime | datetime | UTC datetime. Only valid when interval is 1m. |
</TabItem>
</Tabs>

47
website/metadata/platform_v4_seo_metadata.json vendored
View File

@@ -2851,53 +2851,6 @@
"index constituents founding year"
]
},
"index.european": {
"title": "european",
"description": "Learn how to retrieve Historical European Indices data using the OBB\n Python library. Understand the available parameters, return values, and data fields.",
"keywords": [
"Historical European Indices",
"python obb index european",
"symbol parameter",
"start_date parameter",
"end_date parameter",
"provider parameter",
"interval parameter",
"returns",
"data",
"date",
"close price",
"open price",
"high price",
"low price",
"utc datetime"
]
},
"index.european_constituents": {
"title": "european_constituents",
"description": "Learn how to get the constituents of select European indices using the\n `obb.index.european_constituents` function in Python. Explore the parameters, return\n values, and data structure.",
"keywords": [
"European Index Constituents",
"European indices",
"python obb.index.european_constituents",
"symbol",
"provider",
"data",
"price",
"open",
"high",
"low",
"close",
"volume",
"prev_close",
"change",
"change percent",
"tick",
"last trade timestamp",
"exchange ID",
"seqno",
"asset type"
]
},
"index.fred": {
"title": "fred",
"description": "Learn how to retrieve Historical Fred Indices close values for selected\n symbols using the OBB Python library. This documentation page provides details on\n the required parameters, their types, and default values. It also explains the structure\n of the returned data and its fields.",